This report describes the results of a study by the U.S. Geological Survey in cooperation with ClearWater Conservancy and the Pennsylvania Department of Environmental Protection to develop a hydrologic model to simulate a water budget and identify areas of greater than average recharge for the Spring Creek Basin in central Pennsylvania. The model was developed to help policy makers, natural resource managers, and the public better understand and manage the water resources in the region. The Groundwater and Surface-water FLOW model (GSFLOW), which is an integration of the Precipitation-Runoff Modeling System (PRMS) and the Modular Groundwater Flow Model (MODFLOW-NWT), was used to simulate surface water and groundwater in the Spring Creek Basin for water years 2000–06. Because the groundwater and surface-water divides for the Spring Creek Basin do not coincide, the study area includes the Nittany Creek Basin and headwaters of the Spruce Creek Basin. The hydrologic model was developed by the use of a stepwise process: (1) develop and calibrate a PRMS model and steady-state MODFLOW-NWT model; (2) re-calibrate the steady-state MODFLOW-NWT model using potential recharge estimates simulated from the PRMS model, and (3) integrate the PRMS and MODFLOW-NWT models into GSFLOW. The individually calibrated PRMS and MODFLOW-NWT models were used as a starting point for the calibration of the fully coupled GSFLOW model. The GSFLOW model calibration was done by comparing observations and corresponding simulated values of streamflow from 11 streamgages and groundwater levels from 16 wells. The cumulative water budget and individual water budgets for water years 2000–06 were simulated by using GSFLOW. The largest source and sink terms are represented by precipitation and evapotranspiration, respectively. For the period simulated, a net surplus in the water budget was computed where inflows exceeded outflows by about 1.7 billion cubic feet (0.47 inches per year over the basin area); storage increased by about the same amount to balance the budget. The rate and distribution of recharge throughout the Spring Creek, Nittany Creek, and Spruce Creek Basins is variable as a result of the high degree of hydrogeologic heterogeneity and karst features. The greatest amount of recharge was simulated in the carbonate-bedrock valley, near the toe slopes of Nittany and Tussey Mountains, in the Scotia Barrens, and along the area coinciding with the Gatesburg Formation. Runoff extremes were observed for water years 2001 (dry year) and 2004 (wet year). Simulated average recharge rates (water reaching the saturated zone as defined in GSFLOW) for 2001 and 2004 were 5.4 in/yr and 22.0 in/yr, respectively. Areas where simulations show large variations in annual recharge between wet and dry years are the same areas where simulated recharge was large. Those areas where rates of groundwater recharge are much higher than average, and are capable of accepting substantially greater quantities of recharge during wet years, might be considered critical for maintaining the flow of springs, stream base flow, or the source of water to supply wells. The slopes of the Bald Eagle, Tussey, and Nittany Mountains are relatively insensitive to variations in recharge, primarily because of reduced infiltration rates and steep slopes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155073","collaboration":"Prepared in cooperation with the Clearwater Conservancy and Pennsylvania Department of Environmental Protection","usgsCitation":"Fulton, J.W., Risser, D.W., Regan, R.S., Walker, J.F., Hunt, R.J., Niswonger, R.G., Hoffman, S.A., and Markstrom, S.L., 2015, Water-budgets and recharge-area simulations for the Spring Creek and Nittany Creek Basins and parts of the Spruce Creek Basin, Centre and Huntingdon Counties, Pennsylvania, Water Years 2000–06: U.S. Geological Survey Scientific Investigations Report 2015–5073, 86 p, https://dx.doi.org/10.3133/sir20155073.","productDescription":"x, 86 p.","numberOfPages":"100","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-006529","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":306786,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5073/coverthb.jpg"},{"id":306791,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5073/sir20155073.pdf","text":"Report","size":"27.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5-83"}],"country":"United States","state":"Pennsylvania","county":"Centre County, Huntingdon County","otherGeospatial":"Nittany Creek Basin, Spring Creek Basin, Spruce Creek Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.7179718017578,\n 40.979898069620155\n ],\n [\n -77.55661010742188,\n 40.86004454780482\n ],\n [\n -77.76466369628905,\n 40.7743018636372\n ],\n [\n -77.87384033203124,\n 40.74205475883487\n ],\n [\n -77.93975830078125,\n 40.706148461723764\n ],\n [\n -78.05648803710938,\n 40.66188943992171\n ],\n [\n -78.11897277832031,\n 40.62385529380968\n ],\n [\n -78.16154479980469,\n 40.59283882963389\n ],\n [\n -78.277587890625,\n 40.643135583312805\n ],\n [\n -78.16497802734375,\n 40.730608477796636\n ],\n [\n -78.01666259765625,\n 40.82212357516945\n ],\n [\n -77.82440185546875,\n 40.9280401053324\n ],\n [\n -77.7179718017578,\n 40.979898069620155\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
http://pa.water.usgs.gov/
This study evaluates the role of the Peclet number as affected by molecular diffusion in transient anomalous transport, which is one of the major knowledge gaps in anomalous transport, by combining Monte Carlo simulations and stochastic model analysis. Two alluvial settings containing either short- or long-connected hydrofacies are generated and used as media for flow and transport modeling. Numerical experiments show that 1) the Peclet number affects both the duration of the power-law segment of tracer breakthrough curves (BTCs) and the transition rate from anomalous to Fickian transport by determining the solute residence time for a given low-permeability layer, 2) mechanical dispersion has a limited contribution to the anomalous characteristics of late-time transport as compared to molecular diffusion due to an almost negligible velocity in floodplain deposits, and 3) the initial source dimensions only enhance the power-law tail of the BTCs at short travel distances. A tempered stable stochastic (TSS) model is then applied to analyze the modeled transport. Applications show that the time-nonlocal parameters in the TSS model relate to the Peclet number, Pe. In particular, the truncation parameter in the TSS model increases nonlinearly with a decrease in Pe due to the decrease of the mean residence time, and the capacity coefficient increases with an increase in molecular diffusion which is probably due to the increase in the number of immobile particles. The above numerical experiments and stochastic analysis therefore reveal that the Peclet number as affected by molecular diffusion controls transient anomalous transport in alluvial aquifer–aquitard complexes.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.jconhyd.2015.04.001","usgsCitation":"Zhang, Y., Green, C., and Tick, G.R., 2015, Peclet number as affected by molecular diffusion controls transient anomalous transport in alluvial aquifer-aquitard complexes: Journal of Contaminant Hydrology, v. 177-178, p. 220-238, https://doi.org/10.1016/j.jconhyd.2015.04.001.","productDescription":"19 p.","startPage":"220","endPage":"238","numberOfPages":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061229","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":471875,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jconhyd.2015.04.001","text":"Publisher Index Page"},{"id":306666,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"177-178","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55cdb1b0e4b08400b1fe13be","contributors":{"authors":[{"text":"Zhang, Yong","contributorId":19029,"corporation":false,"usgs":true,"family":"Zhang","given":"Yong","affiliations":[],"preferred":false,"id":567493,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Green, Christopher T. ctgreen@usgs.gov","contributorId":146339,"corporation":false,"usgs":true,"family":"Green","given":"Christopher T.","email":"ctgreen@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":567492,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tick, Geoffrey R.","contributorId":146340,"corporation":false,"usgs":false,"family":"Tick","given":"Geoffrey","email":"","middleInitial":"R.","affiliations":[{"id":16675,"text":"U Alabama","active":true,"usgs":false}],"preferred":false,"id":567494,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70155509,"text":"sir20155106 - 2015 - Hydrologic budget and conditions of Permian, Pennsylvanian, and Mississippian aquifers in the Appalachian Plateaus physiographic province","interactions":[],"lastModifiedDate":"2015-10-26T14:28:11","indexId":"sir20155106","displayToPublicDate":"2015-08-12T15:45:00","publicationYear":"2015","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":"2015-5106","title":"Hydrologic budget and conditions of Permian, Pennsylvanian, and Mississippian aquifers in the Appalachian Plateaus physiographic province","docAbstract":"In response to challenges to groundwater availability posed by historic land-use practices, expanding development of hydrocarbon resources, and drought, the U.S. Geological Survey Groundwater Resources Program began a regional assessment of the Appalachian Plateaus aquifers in 2013 that incorporated a hydrologic landscape approach to estimate all components of the hydrologic system: surface runoff, base flow from groundwater, and interaction with atmospheric water (precipitation and evapotranspiration). This assessment was intended to complement other Federal and State investigations and provide foundational groundwater-related datasets in the Appalachian Plateaus.
\nA regional Soil-Water-Balance model was constructed for a 160,000-square-mile study area that extended to the topographic divide of all streams originating outside but flowing into areas underlain by Appalachian Plateaus aquifers. The model incorporated soil, landscape, and climate variables to estimate an annual water budget for the 32-year period from 1980 to 2011 and was calibrated using base-flow data estimated by hydrograph separation techniques from 20 streamflow gaging stations across the study area. Over this period, an average of 47 inches per year (in/yr) of precipitation fell on Appalachian Plateaus aquifers. Simulations from the regional Soil-Water-Balance model indicate that only 19 percent of the precipitation or an average 9 in/yr recharged aquifers, and 19 percent resulted in surface runoff to streams. The remaining 62 percent, an average of 27 in/yr of water, was returned to the atmosphere via evapotranspiration. Because withdrawals from aquifers due to pumping equated to less than 1 percent of the water budget, differences in predevelopment and postdevelopment regional water budgets of the Appalachian Plateaus were minimal. Storage changes caused by filling of abandoned coal-mine aquifers and long-term differences in aquifer storage resulting from climate fluctuations constitute a small portion of the overall water budget.
\nThe percentage of precipitation that results in recharge, runoff, or evapotranspiration from the landscape varies annually by up to a factor of two depending on temporal changes in prevailing climate conditions and spatial changes in basin characteristics, precipitation patterns, and sources of atmospheric moisture over a large study area. A comparison of water-budget estimates from the regional Soil-Water-Balance model for a dry year (1988) and wet year (2004) showed that evapotranspiration accounts for most of the annual differences in precipitation. As a portion of annual precipitation, evapotranspiration ranged from 69 percent (dry year) to 52 percent (wet year), a range four times greater than the 15 percent (dry year) to 18 percent (wet year) range estimated for recharge. Evapotranspiration as a percentage of precipitation peaks during dry periods, whereas base flow and runoff tend to reach minimum values. During wet periods, this relationship is reversed and base flow and runoff as a percentage of precipitation generally peak while evapotranspiration percentages reach minimum values. Annual recharge in the Appalachian Plateaus reaches a maximum at near 20 percent of annual precipitation, regardless of the severity of wet conditions.
\nHydrograph separation data from 849 streamflow gaging stations in the study area were used to assess trends in streamflow, base flow, surface runoff, and base-flow index, or ratio of base flow to streamflow, in the Appalachian Plateaus for the period from 1930 to 2011. Annual data anomalies for each of the four variables were individually defined as the annual standard deviation from the mean at all 849 streamflow gaging stations. Annual data anomalies confirm the close relation of annual precipitation to both base flow and runoff components of streamflow, and both components increased during the period of analysis. Around 1970, conditions shifted streamflow from values generally below to above long-term means. At a regional scale, increases in base flow account for most of these observed increases in mean annual streamflow. The independence of the base-flow index to annual climate trends indicate that changes in the components of streamflow of the Appalachian Plateaus are probably in response to shifts in seasonal precipitation or widespread land-use practices.
\nA subset of 77 index streamgages, defined as having 60 or more years of complete record between the years 1930 and 2011 with no more than 20 percent missing data, was selected to show spatial patterns of change in the water budget. Data from the index streamgages showed that the overall trends in base flow are dependent upon the period of evaluation. Long-term (1930–2011) increases in base flow were observed throughout the study area. For two shorter periods (1930–1969 and 1970–2011) trends in base flow were largely negative. In general, spatial patterns of change in streamflow, base flow, and runoff were mixed but generally consistent with prevailing climate patterns and land-use changes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155106","collaboration":"Groundwater Resources Program","usgsCitation":"McCoy, K.J., Yager, R.M., Nelms, D.L., Ladd, D.E., Monti, Jack, Jr., and Kozar, M.D., 2015, Hydrologic budget and conditions of Permian, Pennsylvanian, and Mississippian aquifers in the Appalachian Plateaus Physiographic Province (ver. 1.1, October 2015): U.S. Geological Survey Scientific Investigations Report 2015–5106, 77 p., https://dx.doi.org/10.3133/sir20155106.","productDescription":"vii, 77 p.","numberOfPages":"90","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060623","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":306582,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5106/sir20155106.pdf","text":"Report","size":"36.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5106"},{"id":306581,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5106/images/coverthb.jpg"},{"id":309929,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2015/5106/versionHist.txt","text":"October 26, 2015","size":"1.06 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2015-5106"}],"country":"United States","state":"Alabama, Kentucky, Maryland, Ohio, Pennslyvania, Virginia, Tennessee, West Virginia","otherGeospatial":"Mississippian aquifer, Pennsylvanian aquifer, Permian aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.31103515625,\n 41.705728515237524\n ],\n [\n -81.2109375,\n 41.83682786072714\n ],\n [\n -82.79296874999999,\n 41.36031866306708\n ],\n [\n -83.8037109375,\n 38.66835610151509\n ],\n [\n -86.98974609375,\n 34.97600151317591\n ],\n [\n -88.22021484375,\n 34.79576153473033\n ],\n [\n -88.39599609375,\n 32.62087018318113\n ],\n [\n -85.4736328125,\n 34.95799531086792\n ],\n [\n -83.3203125,\n 36.5978891330702\n ],\n [\n -80.22216796875,\n 37.474858084971046\n ],\n [\n -78.5302734375,\n 39.707186656826565\n ],\n [\n -76.31103515625,\n 41.705728515237524\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted August 13, 2015; Version 1.1: October 26, 2015","contact":"Director, Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, VA 23228
http://va.water.usgs.gov
In October 2012, the U.S. Geological Survey (USGS), in cooperation with the Central Texas Groundwater Conservation District, began an assessment to better understand if and where groundwater from the Ellenburger-San Saba aquifer is discharging to the Colorado River, and if and where Colorado River streamflow is recharging the Ellenburger-San Saba aquifer in the study area. Discharge measurements were made to determine if different reaches of the Colorado River in northwestern Burnet and southeastern San Saba Counties are gaining or losing streamflow, the locations and quantities of gains and losses, and whether the gains and losses can be attributed to interaction between the river and the Ellenbuger-San Saba aquifer. To assess streamflow gains and losses, two sets of synoptic gain-loss discharge measurements representing different streamflow conditions were completed. In the first gain-loss streamflow survey during December 3–6, 2012 (hereinafter the fall 2012 gain-loss survey), discharge measurements were made at low-flow conditions ranging from about 30 to 60 cubic feet per second (ft3/s) at seven locations along the Colorado River. In the second gain-loss streamflow survey during May 31–June 1, 2014 (hereinafter the spring 2014 gain-loss survey), discharge measurements were made at high-flow conditions ranging from about 660 to 900 ft3/s at 12 locations along the Colorado River.
\nDuring the fall 2012 gain-loss survey, verifiable gains or losses of streamflow were identified in 4 of 6 reaches (the difference in measured discharge between the upstream and downstream boundaries of the reach was larger than the sum of potential errors associated with the two discharge measurements). The two reaches with a verifiable gain in streamflow cross areas where the Ellenburger-San Saba aquifer crops out. The more upstream of the two reaches with verifiable losses crosses a small part of the Ellenburger-San Saba aquifer outcrop and confining units (Point Peak Member and Morgan Creek Limestone); it is possible streamflow losses in this reach are in the form of recharge to the Ellenburger-San Saba aquifer; little streamflow is likely lost to the underlying formations in the downstream part of the reach, which consists of relatively impermeable aquifer confining units exposed at land surface. The more downstream of the two reaches where a verifiable loss of streamflow was measured also flows across relatively impermeable confining units before crossing the Mid-Cambrian aquifer outcrop in the lower part of the reach; most of the streamflow losses in this reach were likely a result of water infiltrating into the subsurface from the streambed and providing recharge to the relatively permeable Mid-Cambrian aquifer.
\nDuring the spring 2014 gain-loss survey, 11 reaches were combined into 3 in an attempt to consolidate gains and losses as well as group reaches within the same hydrogeologic units. An unverifiable loss was measured in the reach farthest upstream, which crosses a combination of alluvium and Ellenburger-San Saba aquifer outcrop, whereas an unverifiable gain was measured in the middle reach, which crosses each of the different hydrogeologic units represented in the study area. The reach farthest downstream crosses an area where only the Ellenburger-San Saba aquifer crops out; a streamflow gain of 123 ft3/s was measured in this reach, exceeding the potential error of 93.9 ft3/s. The verifiable streamflow gain in this downstream reach implies the Ellenburger-San Saba aquifer was discharging groundwater to the Colorado River in this part of the study area under the hydrologic conditions of the spring 2014 gain-loss survey.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155098","collaboration":"Prepared in cooperation with the Central Texas Groundwater Conservation District","usgsCitation":"Braun, C.L., and Grzyb, S.D., 2015, Streamflow gains and losses in the Colorado River in northwestern Burnet and southeastern San Saba Counties, Texas, 2012–14: U.S. Geological Survey Scientific Investigations Report 2015–5098, 32 p., https://dx.doi.org/10.3133/sir20155098.","productDescription":"v, 32 p.","numberOfPages":"41","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-062274","costCenters":[{"id":105,"text":"Alabama Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":306566,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5098/coverthb.jpg"},{"id":306567,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5098/sir20155098.pdf","text":"Report","size":"6.48 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5098"}],"country":"United States","state":"Texas","county":"Burnet County, San Saba County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.48075866699219,\n 30.918131046738022\n ],\n [\n -98.48075866699219,\n 31.0376384361344\n ],\n [\n -98.38085174560547,\n 31.0376384361344\n ],\n [\n -98.38085174560547,\n 30.918131046738022\n ],\n [\n -98.48075866699219,\n 30.918131046738022\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, Texas 78754–4501
http://tx.usgs.gov/
Hydraulically fractured shales are becoming an increasingly important source of natural gas production in the United States. This process has been known to create up to 420 gallons of produced water (PW) per day, but the volume varies depending on the formation, and the characteristics of individual hydraulic fracture. PW from hydraulic fracturing of shales are comprised of injected fracturing fluids and natural formation waters in proportions that change over time. Across the state of Pennsylvania, shale gas production is booming; therefore, it is important to assess the variability in PW chemistry and microbiology across this geographical span. We quantified the inorganic and organic chemical composition and microbial communities in PW samples from 13 shale gas wells in north central Pennsylvania. Microbial abundance was generally low (66–9400 cells/mL). Non-volatile dissolved organic carbon (NVDOC) was high (7–31 mg/L) relative to typical shallow groundwater, and the presence of organic acid anions (e.g., acetate, formate, and pyruvate) indicated microbial activity. Volatile organic compounds (VOCs) were detected in four samples (∼1 to 11.7 μg/L): benzene and toluene in the Burket sample, toluene in two Marcellus samples, and tetrachloroethylene (PCE) in one Marcellus sample. VOCs can be either naturally occurring or from industrial activity, making the source of VOCs unclear. Despite the addition of biocides during hydraulic fracturing, H2S-producing, fermenting, and methanogenic bacteria were cultured from PW samples. The presence of culturable bacteria was not associated with salinity or location; although organic compound concentrations and time in production were correlated with microbial activity. Interestingly, we found that unlike the inorganic chemistry, PW organic chemistry and microbial viability were highly variable across the 13 wells sampled, which can have important implications for the reuse and handling of these fluids
","language":"English","publisher":"Oxford","publisherLocation":"New York, NY","doi":"10.1016/j.apgeochem.2015.04.011","usgsCitation":"Akob, D.M., Cozzarelli, I.M., Dunlap, D.S., Rowan, E.L., and Lorah, M.M., 2015, Organic and inorganic composition and microbiology of produced waters from Pennsylvania shale gas wells: Applied Geochemistry, v. 60, p. 116-125, https://doi.org/10.1016/j.apgeochem.2015.04.011.","productDescription":"10 p.","startPage":"116","endPage":"125","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061928","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":306602,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","county":"Lycoming, 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U.S.A.","interactions":[],"lastModifiedDate":"2017-01-11T15:38:09","indexId":"70155823","displayToPublicDate":"2015-08-11T13:00:00","publicationYear":"2015","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":"Understory vegetation as an indicator for floodplain forest restoration in the Mississippi River Alluvial Valley, U.S.A.","docAbstract":"In the Mississippi River Alluvial Valley (MAV), complete alteration of river-floodplain hydrology allowed for widespread
conversion of forested bottomlands to intensive agriculture, resulting in nearly 80% forest loss. Governmental programs have
attempted to restore forest habitat and functions within this altered landscape by the methods of tree planting (afforestation)
and local hydrologic enhancement on reclaimed croplands. Early assessments identified factors that influenced whether
planting plus tree colonization could establish an overstory community similar to natural bottomland forests. The extent
to which afforested sites develop typical understory vegetation has not been evaluated, yet understory composition may be
indicative of restored site conditions. As part of a broad study quantifying the ecosystem services gained from restoration
efforts, understory vegetation was compared between 37 afforested sites and 26 mature forest sites. Differences in vegetation
attributes for species growth forms, wetland indicator classes, and native status were tested with univariate analyses;
floristic composition data were analyzed by multivariate techniques. Understory vegetation of restoration sites was generally
hydrophytic, but species composition differed from that of mature bottomland forest because of young successional age and
differing responses of plant growth forms. Attribute and floristic variation among restoration sites was related to variation
in canopy development and local wetness conditions, which in turn reflected both intrinsic site features and outcomes of
restoration practices. Thus, understory vegetation is a useful indicator of functional progress in floodplain forest restoration.
Storms following wildfires are known to impair drinking water supplies in the southwestern United States, yet our understanding of the role of precipitation in post-wildfire water quality is far from complete. We quantitatively assessed water-quality impacts of different hydrologic events in the Colorado Front Range and found that for a three-year period, substantial hydrologic and geochemical responses downstream of a burned area were primarily driven by convective storms with a 30 min rainfall intensity >10 mm h−1. These storms, which typically occur several times each year in July–September, are often small in area, short-lived, and highly variable in intensity and geographic distribution. Thus, a rain gage network with high temporal resolution and spatial density, together with high-resolution stream sampling, are required to adequately characterize post-wildfire responses. We measured total suspended sediment, dissolved organic carbon (DOC), nitrate, and manganese concentrations that were 10–156 times higher downstream of a burned area compared to upstream during relatively common (50% annual exceedance probability) rainstorms, and water quality was sufficiently impaired to pose water-treatment concerns. Short-term water-quality impairment was driven primarily by increased surface runoff during higher intensity convective storms that caused erosion in the burned area and transport of sediment and chemical constituents to streams. Annual sediment yields downstream of the burned area were controlled by storm events and subsequent remobilization, whereas DOC yields were closely linked to annual runoff and thus were more dependent on interannual variation in spring runoff. Nitrate yields were highest in the third year post-wildfire. Results from this study quantitatively demonstrate that water quality can be altered for several years after wildfire. Because the southwestern US is prone to wildfires and high-intensity rain storms, the role of storms in post-wildfire water-quality impacts must be considered when assessing water-quality vulnerability.
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Updated peak-flow frequency estimates for 262 streamflow-gaging stations were developed using data through 2009 and log-Pearson Type III procedures outlined by the Hydrology Subcommittee of the Interagency Advisory Committee on Water Data. An average generalized skew coefficient was determined for three hydrologic zones in North Dakota. A StreamStats web application was developed to estimate basin characteristics for the regional regression equation analysis. Methods for estimating a weighted peak-flow frequency for gaged sites and ungaged sites are presented.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155096","collaboration":"Prepared in cooperation with the North Dakota State Water Commision, the North Dakota Department of Transportation, the North Dakota Department of Health, the Red River Joint Water Resources Board, and the Devils Lake Basin Joint Water Resource Board","usgsCitation":"Williams-Sether, Tara, 2015, Regional regression equations to estimate peak-flow frequency at sites in North Dakota using data through 2009: U.S. Geological Survey Scientific Investigations Report 2015–5096, 12 p.,\nhttps://dx.doi.org/10.3133/sir20155096.","productDescription":"Report: iv, 12 p.; 4 Tables","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-057778","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":306455,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5096/sir20155096.pdf","text":"Report","size":"4.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5096"},{"id":306456,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2015/5096/downloads","text":"Tables 1 and 4","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5096 Tables 1 and 4"},{"id":306454,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5096/coverthb.jpg"}],"country":"United States","state":"North Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.56982421875,\n 45.920587344733654\n ],\n [\n -96.591796875,\n 46.37725420510028\n ],\n [\n -96.78955078125,\n 46.6795944656402\n ],\n [\n -96.8115234375,\n 46.965259400349275\n ],\n [\n -96.85546875,\n 47.69497434186282\n ],\n [\n -97.0751953125,\n 48.06339653776211\n ],\n [\n -97.1630859375,\n 48.516604348867475\n ],\n [\n -97.09716796875,\n 48.748945343432936\n ],\n [\n -97.2509765625,\n 49.023461463214126\n ],\n [\n -104.08447265624999,\n 49.009050809382046\n ],\n [\n -104.04052734375,\n 45.9511496866914\n ],\n [\n -96.56982421875,\n 45.920587344733654\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, North Dakota Water Science Center
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Recent advances in fluorometry have led to increased use of rhodamine WT as a tracer in streams and rivers. In light of this increased use, a review of the dye's behavior in freshwater systems is presented. Studies in the groundwater literature indicate that rhodamine WT is transported nonconservatively, with sorption removing substantial amounts of tracer mass. Column studies document a two-step breakthrough curve in which two structural isomers are chromatographically separated. Although the potential for nonconservative transport is acknowledged in the surface water literature, many studies assume that sorptive losses will not affect the characterization of physical transport processes. A literature review and modeling analysis indicates that this assumption is valid for quantification of physical properties that are based on the bulk of the tracer mass (traveltime), and invalid for the characterization of processes represented by the tracer tail (transient storage attributable to hyporheic exchange). Rhodamine WT should be considered nonconservative in the hyporheic zone due to nonconservative behavior demonstrated for similar conditions in groundwater. As such, rhodamine WT should not be used as a quantitative tracer in hyporheic zone investigations, including the study of long flow paths and the development of models describing hyporheic zone processes. Rhodamine WT may be used to qualitatively characterize storage in large systems, where there are few practical alternatives. Qualitative investigations should rely on early portions of the tracer profile, making use of the temporal resolution afforded by in situ fluorometry, while discarding later parts of the tracer profile that are adversely affected by sorption.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2015WR017201","usgsCitation":"Runkel, R.L., 2015, On the use of rhodamine WT for the characterization of stream hydrodynamics and transient storage: Water Resources Research, v. 51, no. 8, p. 6125-6142, https://doi.org/10.1002/2015WR017201.","productDescription":"18 p.","startPage":"6125","endPage":"6142","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064798","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":471890,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015wr017201","text":"Publisher Index Page"},{"id":309527,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-06","publicationStatus":"PW","scienceBaseUri":"560faacce4b0ba4884c5eec7","chorus":{"doi":"10.1002/2015wr017201","url":"http://dx.doi.org/10.1002/2015wr017201","publisher":"Wiley-Blackwell","authors":"Runkel Robert L.","journalName":"Water Resources Research","publicationDate":"8/2015","auditedOn":"7/24/2015"},"contributors":{"authors":[{"text":"Runkel, Robert L. 0000-0003-3220-481X runkel@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-481X","contributorId":685,"corporation":false,"usgs":true,"family":"Runkel","given":"Robert","email":"runkel@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":576220,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70155807,"text":"70155807 - 2015 - Optimizing fish sampling for fish - mercury bioaccumulation factors","interactions":[],"lastModifiedDate":"2018-08-09T12:36:18","indexId":"70155807","displayToPublicDate":"2015-08-01T13:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1226,"text":"Chemosphere","active":true,"publicationSubtype":{"id":10}},"title":"Optimizing fish sampling for fish - mercury bioaccumulation factors","docAbstract":"Fish Bioaccumulation Factors (BAFs; ratios of mercury (Hg) in fish (Hgfish) and water (Hgwater)) are used to develop Total Maximum Daily Load and water quality criteria for Hg-impaired waters. Both applications require representative Hgfish estimates and, thus, are sensitive to sampling and data-treatment methods. Data collected by fixed protocol from 11 streams in 5 states distributed across the US were used to assess the effects of Hgfish normalization/standardization methods and fish sample numbers on BAF estimates. Fish length, followed by weight, was most correlated to adult top-predator Hgfish. Site-specific BAFs based on length-normalized and standardized Hgfish estimates demonstrated up to 50% less variability than those based on non-normalized Hgfish. Permutation analysis indicated that length-normalized and standardized Hgfish estimates based on at least 8 trout or 5 bass resulted in mean Hgfish coefficients of variation less than 20%. These results are intended to support regulatory mercury monitoring and load-reduction program improvements.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemosphere.2014.12.068","usgsCitation":"Scudder Eikenberry, B.C., Riva-Murray, K., Knightes, C.D., Journey, C.A., Chasar, L., Brigham, M.E., and Bradley, P.M., 2015, Optimizing fish sampling for fish - mercury bioaccumulation factors: Chemosphere, v. 135, p. 467-473, https://doi.org/10.1016/j.chemosphere.2014.12.068.","productDescription":"7 p.","startPage":"467","endPage":"473","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-044433","costCenters":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":471902,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemosphere.2014.12.068","text":"Publisher Index Page"},{"id":306540,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"135","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55c9cb37e4b08400b1fdb71e","contributors":{"authors":[{"text":"Scudder Eikenberry, Barbara C.","contributorId":63771,"corporation":false,"usgs":true,"family":"Scudder Eikenberry","given":"Barbara","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":572326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Riva-Murray, Karen 0000-0001-6683-2238 krmurray@usgs.gov","orcid":"https://orcid.org/0000-0001-6683-2238","contributorId":2984,"corporation":false,"usgs":true,"family":"Riva-Murray","given":"Karen","email":"krmurray@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":566400,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knightes, Christopher D.","contributorId":32666,"corporation":false,"usgs":true,"family":"Knightes","given":"Christopher","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":566403,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Journey, Celeste A. 0000-0002-2284-5851 cjourney@usgs.gov","orcid":"https://orcid.org/0000-0002-2284-5851","contributorId":2617,"corporation":false,"usgs":true,"family":"Journey","given":"Celeste","email":"cjourney@usgs.gov","middleInitial":"A.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":566404,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chasar, Lia C.","contributorId":52905,"corporation":false,"usgs":true,"family":"Chasar","given":"Lia C.","affiliations":[],"preferred":false,"id":566399,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brigham, Mark E. 0000-0001-7412-6800 mbrigham@usgs.gov","orcid":"https://orcid.org/0000-0001-7412-6800","contributorId":1840,"corporation":false,"usgs":true,"family":"Brigham","given":"Mark","email":"mbrigham@usgs.gov","middleInitial":"E.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":566401,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":566402,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70157111,"text":"70157111 - 2015 - Ground-truthing electrical resistivity methods in support of submarine groundwater discharge studies: Examples from Hawaii, Washington, and California","interactions":[],"lastModifiedDate":"2025-05-13T16:54:57.840505","indexId":"70157111","displayToPublicDate":"2015-08-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3928,"text":"Journal of Environmental & Engineering Geophysics","printIssn":"1083-1363","active":true,"publicationSubtype":{"id":10}},"title":"Ground-truthing electrical resistivity methods in support of submarine groundwater discharge studies: Examples from Hawaii, Washington, and California","docAbstract":"Submarine groundwater discharge (SGD) is an important conduit that links terrestrial and marine environments. SGD conveys both water and water-borne constituents into coastal waters, where these inflows may impact near-shore ecosystem health and sustainability. Multichannel electrical resistivity techniques have proven to be a powerful tool to examine scales and dynamics of SGD and SGD forcings. However, there are uncertainties both in data aquisition and data processing that must be addressed to maximize the effectiveness of this tool in estuarine or marine environments. These issues most often relate to discerning subtle nuances in the flow of electricity through variably saturated media that can also be highly conductive (i.e., seawater).
\nThree contrasting field sites were examined for this study to assess the effectiveness of electrical resistivity techniques in varying coastal settings by comparing resistivity data to direct salinity and resistivity observations, quantifying changes in lithology and beach geomorphology, and fine-tuning inversion protocols. The three study sites all have substantial (up to 85 cm day−1) submarine groundwater discharge rates, but the hydrologic, oceanographic, and geologic characteristics of the sites are all very different. At a site in Pelekane Bay on the Big Island of Hawaii, seasonal flooding introduces very high concentrations of fine to coarse sediment into the bay. Near-shore circulation is limited in Pelekane Bay, so this newly introduced sediment can become deposited in the bay where it accumulates over time. At a site in Hood Canal, a fjord within Puget Sound, Washington, SGD rates can be high because of the large tidal range, abundant recharge, and steep hydrologic gradients. At Younger Lagoon in northern California, the flow of groundwater towards the coast is much more parsimonious, but here marine processes, including recirculated seawater, are important in controlling the flow of material towards the coast.
\nRigorous ground-truthing at each field site showed that multi-channel electrcial resistivity techniques can reproduce the scales and dynamics of a seepage field when such data are correctly collected, and when the model inversions are tuned to field site characteristics. Such information can provide a unique perspective on the scales and dynamics of exchange processes within a coastal aquifer—information essential to scientists and resource managers alike.
","language":"English","publisher":"Environmental and Engineering Geophysical Society","publisherLocation":"Englewood, CO","doi":"10.2113/JEEG20.1.81","usgsCitation":"Johnson, C., Swarzenski, P.W., Richardson, C.M., Smith, C.G., Kroeger, K.D., and Ganguli, P.M., 2015, Ground-truthing electrical resistivity methods in support of submarine groundwater discharge studies: Examples from Hawaii, Washington, and California: Journal of Environmental & Engineering Geophysics, v. 20, no. 1, p. 81-87, https://doi.org/10.2113/JEEG20.1.81.","productDescription":"7 p.","startPage":"81","endPage":"87","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061829","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":308201,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Hawaii, Washington","otherGeospatial":"Hood Canal, Pelekane Bay, Puget Sound, Younger Lagoon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.1842041015625,\n 47.28295557691231\n ],\n [\n -123.1842041015625,\n 47.95314495015594\n ],\n [\n -122.4920654296875,\n 47.95314495015594\n ],\n [\n -122.4920654296875,\n 47.28295557691231\n ],\n [\n -123.1842041015625,\n 47.28295557691231\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.01959228515625,\n 19.83906000930461\n ],\n [\n -156.01959228515625,\n 20.19905717998772\n ],\n [\n -155.79849243164062,\n 20.19905717998772\n ],\n [\n -155.79849243164062,\n 19.83906000930461\n ],\n [\n -156.01959228515625,\n 19.83906000930461\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.06909179687501,\n 36.935623193306064\n ],\n [\n -122.06909179687501,\n 36.98390610968992\n ],\n [\n -121.96197509765625,\n 36.98390610968992\n ],\n [\n -121.96197509765625,\n 36.935623193306064\n ],\n [\n -122.06909179687501,\n 36.935623193306064\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55fa92bde4b05d6c4e501a90","contributors":{"authors":[{"text":"Johnson, Cordell 0000-0001-8353-8030 cordell_johnson@usgs.gov","orcid":"https://orcid.org/0000-0001-8353-8030","contributorId":147437,"corporation":false,"usgs":true,"family":"Johnson","given":"Cordell","email":"cordell_johnson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":571692,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swarzenski, Peter W. 0000-0003-0116-0578 pswarzen@usgs.gov","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":1070,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Peter","email":"pswarzen@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":571691,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richardson, Christina M. 0000-0003-0597-8836","orcid":"https://orcid.org/0000-0003-0597-8836","contributorId":147438,"corporation":false,"usgs":false,"family":"Richardson","given":"Christina","email":"","middleInitial":"M.","affiliations":[{"id":6948,"text":"UC Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":571693,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Christopher G. 0000-0002-8075-4763 cgsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":3410,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher","email":"cgsmith@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":571694,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kroeger, Kevin D. 0000-0002-4272-2349 kkroeger@usgs.gov","orcid":"https://orcid.org/0000-0002-4272-2349","contributorId":1603,"corporation":false,"usgs":true,"family":"Kroeger","given":"Kevin","email":"kkroeger@usgs.gov","middleInitial":"D.","affiliations":[{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"preferred":true,"id":571695,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ganguli, Priya M.","contributorId":147439,"corporation":false,"usgs":false,"family":"Ganguli","given":"Priya","email":"","middleInitial":"M.","affiliations":[{"id":6948,"text":"UC Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":571696,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70198333,"text":"70198333 - 2015 - Potential for real‐time understanding of coupled hydrologic and biogeochemical processes in stream ecosystems: Future integration of telemetered data with process models for glacial meltwater streams","interactions":[],"lastModifiedDate":"2021-04-07T13:54:57.888253","indexId":"70198333","displayToPublicDate":"2015-07-30T15:30:13","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Potential for real‐time understanding of coupled hydrologic and biogeochemical processes in stream ecosystems: Future integration of telemetered data with process models for glacial meltwater streams","docAbstract":"While continuous monitoring of streamflow and temperature has been common for some time, there is great potential to expand continuous monitoring to include water quality parameters such as nutrients, turbidity, oxygen, and dissolved organic material. In many systems, distinguishing between watershed and stream ecosystem controls can be challenging. The usefulness of such monitoring can be enhanced by the application of quantitative models to interpret observed patterns in real time. Examples are discussed primarily from the glacial meltwater streams of the McMurdo Dry Valleys, Antarctica. Although the Dry Valley landscape is barren of plants, many streams harbor thriving cyanobacterial mats. Whereas a daily cycle of streamflow is controlled by the surface energy balance on the glaciers and the temporal pattern of solar exposure, the daily signal for biogeochemical processes controlling water quality is generated along the stream. These features result in an excellent outdoor laboratory for investigating fundamental ecosystem process and the development and validation of process‐based models. As part of the McMurdo Dry Valleys Long‐Term Ecological Research project, we have conducted field experiments and developed coupled biogeochemical transport models for the role of hyporheic exchange in controlling weathering reactions, microbial nitrogen cycling, and stream temperature regulation. We have adapted modeling approaches from sediment transport to understand mobilization of stream biomass with increasing flows. These models help to elucidate the role of in‐stream processes in systems where watershed processes also contribute to observed patterns, and may serve as a test case for applying real‐time stream ecosystem models.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015WR017618","usgsCitation":"McKnight, D.M., Cozzetto, K.D., Cullis, J.D., Gooseff, M.N., Jaros, C., Koch, J.C., Lyons, W.B., Neupauer, R.M., and Wlostowski, A.N., 2015, Potential for real‐time understanding of coupled hydrologic and biogeochemical processes in stream ecosystems: Future integration of telemetered data with process models for glacial meltwater streams: Water Resources Research, v. 51, no. 8, p. 6725-6738, https://doi.org/10.1002/2015WR017618.","productDescription":"14 p.","startPage":"6725","endPage":"6738","ipdsId":"IP-066061","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":490051,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015wr017618","text":"Publisher Index Page"},{"id":356008,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"McMurdo Dry Valleys, Antarctica","volume":"51","issue":"8","noUsgsAuthors":false,"publicationDate":"2015-08-30","publicationStatus":"PW","scienceBaseUri":"5b6fcbc1e4b0f5d57878ecbe","contributors":{"authors":[{"text":"McKnight, Diane M.","contributorId":59773,"corporation":false,"usgs":false,"family":"McKnight","given":"Diane","email":"","middleInitial":"M.","affiliations":[{"id":16833,"text":"INSTAAR, University of Colorado","active":true,"usgs":false}],"preferred":false,"id":741115,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cozzetto, Karen D.","contributorId":44461,"corporation":false,"usgs":true,"family":"Cozzetto","given":"Karen","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":741116,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cullis, James D. S.","contributorId":206559,"corporation":false,"usgs":false,"family":"Cullis","given":"James","email":"","middleInitial":"D. S.","affiliations":[],"preferred":false,"id":741117,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gooseff, Michael N.","contributorId":71880,"corporation":false,"usgs":true,"family":"Gooseff","given":"Michael","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":741118,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jaros, Christopher","contributorId":206566,"corporation":false,"usgs":false,"family":"Jaros","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":741119,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":741120,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lyons, W. Berry","contributorId":73497,"corporation":false,"usgs":true,"family":"Lyons","given":"W.","email":"","middleInitial":"Berry","affiliations":[],"preferred":false,"id":741121,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Neupauer, Roseanna M.","contributorId":176580,"corporation":false,"usgs":false,"family":"Neupauer","given":"Roseanna","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":741122,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wlostowski, Adam N. 0000-0001-5703-9916","orcid":"https://orcid.org/0000-0001-5703-9916","contributorId":191365,"corporation":false,"usgs":false,"family":"Wlostowski","given":"Adam","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":741123,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70144397,"text":"70144397 - 2015 - Evaluating the importance of characterizing soil structure and horizons in parameterizing a hydrologic process model","interactions":[],"lastModifiedDate":"2016-01-25T08:55:36","indexId":"70144397","displayToPublicDate":"2015-07-29T10:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the importance of characterizing soil structure and horizons in parameterizing a hydrologic process model","docAbstract":"Incorporating the influence of soil structure and horizons into parameterizations of distributed surface water/groundwater models remains a challenge. Often, only a single soil unit is employed, and soil-hydraulic properties are assigned based on textural classification, without evaluating the potential impact of these simplifications. This study uses a distributed physics-based model to assess the influence of soil horizons and structure on effective parameterization. This paper tests the viability of two established and widely used hydrogeologic methods for simulating runoff and variably saturated flow through layered soils: (1) accounting for vertical heterogeneity by combining hydrostratigraphic units with contrasting hydraulic properties into homogeneous, anisotropic units and (2) use of established pedotransfer functions based on soil texture alone to estimate water retention and conductivity, without accounting for the influence of pedon structures and hysteresis. The viability of this latter method for capturing the seasonal transition from runoff-dominated to evapotranspiration-dominated regimes is also tested here. For cases tested here, event-based simulations using simplified vertical heterogeneity did not capture the state-dependent anisotropy and complex combinations of runoff generation mechanisms resulting from permeability contrasts in layered hillslopes with complex topography. Continuous simulations using pedotransfer functions that do not account for the influence of soil structure and hysteresis generally over-predicted runoff, leading to propagation of substantial water balance errors. Analysis suggests that identifying a dominant hydropedological unit provides the most acceptable simplification of subsurface layering and that modified pedotransfer functions with steeper soil-water retention curves might adequately capture the influence of soil structure and hysteresis on hydrologic response in headwater catchments.
","language":"English","publisher":"Wiley","publisherLocation":"Chichester, Sussex","doi":"10.1002/hyp.10592","usgsCitation":"Mirus, B.B., 2015, Evaluating the importance of characterizing soil structure and horizons in parameterizing a hydrologic process model: Hydrological Processes, v. 29, p. 4611-4623, https://doi.org/10.1002/hyp.10592.","productDescription":"13 p.","startPage":"4611","endPage":"4623","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064649","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":314717,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-29","publicationStatus":"PW","scienceBaseUri":"56a75553e4b0b28f1184d829","contributors":{"authors":[{"text":"Mirus, Benjamin B. 0000-0001-5550-014X bbmirus@usgs.gov","orcid":"https://orcid.org/0000-0001-5550-014X","contributorId":4064,"corporation":false,"usgs":true,"family":"Mirus","given":"Benjamin","email":"bbmirus@usgs.gov","middleInitial":"B.","affiliations":[{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":543574,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70155132,"text":"70155132 - 2015 - Evaluation of habitat suitability index models by global sensitivity and uncertainty analyses: a case study for submerged aquatic vegetation","interactions":[],"lastModifiedDate":"2015-07-29T15:48:16","indexId":"70155132","displayToPublicDate":"2015-07-29T04:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of habitat suitability index models by global sensitivity and uncertainty analyses: a case study for submerged aquatic vegetation","docAbstract":"Habitat suitability index (HSI) models are commonly used to predict habitat quality and species distributions and are used to develop biological surveys, assess reserve and management priorities, and anticipate possible change under different management or climate change scenarios. Important management decisions may be based on model results, often without a clear understanding of the level of uncertainty associated with model outputs. We present an integrated methodology to assess the propagation of uncertainty from both inputs and structure of the HSI models on model outputs (uncertainty analysis: UA) and relative importance of uncertain model inputs and their interactions on the model output uncertainty (global sensitivity analysis: GSA). We illustrate the GSA/UA framework using simulated hydrology input data from a hydrodynamic model representing sea level changes and HSI models for two species of submerged aquatic vegetation (SAV) in southwest Everglades National Park: Vallisneria americana (tape grass) and Halodule wrightii (shoal grass). We found considerable spatial variation in uncertainty for both species, but distributions of HSI scores still allowed discrimination of sites with good versus poor conditions. Ranking of input parameter sensitivities also varied spatially for both species, with high habitat quality sites showing higher sensitivity to different parameters than low-quality sites. HSI models may be especially useful when species distribution data are unavailable, providing means of exploiting widely available environmental datasets to model past, current, and future habitat conditions. The GSA/UA approach provides a general method for better understanding HSI model dynamics, the spatial and temporal variation in uncertainties, and the parameters that contribute most to model uncertainty. Including an uncertainty and sensitivity analysis in modeling efforts as part of the decision-making framework will result in better-informed, more robust decisions.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.1520","usgsCitation":"Zajac, Z., Stith, B., Bowling, A.C., Langtimm, C.A., and Swain, E.D., 2015, Evaluation of habitat suitability index models by global sensitivity and uncertainty analyses: a case study for submerged aquatic vegetation: Ecology and Evolution, v. 5, no. 13, p. 2503-2517, https://doi.org/10.1002/ece3.1520.","productDescription":"15 p.","startPage":"2503","endPage":"2517","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053424","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":471925,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.1520","text":"Publisher Index Page"},{"id":306252,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.36474609375,\n 25.090573819461\n ],\n [\n -81.36474609375,\n 25.84439325019514\n ],\n [\n -80.8154296875,\n 25.84439325019514\n ],\n [\n -80.8154296875,\n 25.090573819461\n ],\n [\n -81.36474609375,\n 25.090573819461\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","issue":"13","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55b9eb1ee4b05b91f6398b37","chorus":{"doi":"10.1002/ece3.1520","url":"http://dx.doi.org/10.1002/ece3.1520","publisher":"Wiley-Blackwell","authors":"Zajac Zuzanna, Stith Bradley, Bowling Andrea C., Langtimm Catherine A., Swain Eric D.","journalName":"Ecology and Evolution","publicationDate":"6/1/2015","auditedOn":"7/24/2015"},"contributors":{"authors":[{"text":"Zajac, Zuzanna","contributorId":145637,"corporation":false,"usgs":false,"family":"Zajac","given":"Zuzanna","email":"","affiliations":[{"id":16181,"text":"University of Florida, Department of Agriculture and Biological Engineering","active":true,"usgs":false}],"preferred":false,"id":564855,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stith, Bradley bstith@usgs.gov","contributorId":3596,"corporation":false,"usgs":true,"family":"Stith","given":"Bradley","email":"bstith@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":564856,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bowling, Andrea C.","contributorId":43615,"corporation":false,"usgs":true,"family":"Bowling","given":"Andrea","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":564857,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Langtimm, Catherine A. 0000-0001-8499-5743 clangtimm@usgs.gov","orcid":"https://orcid.org/0000-0001-8499-5743","contributorId":3045,"corporation":false,"usgs":true,"family":"Langtimm","given":"Catherine","email":"clangtimm@usgs.gov","middleInitial":"A.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":564854,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swain, Eric D. 0000-0001-7168-708X edswain@usgs.gov","orcid":"https://orcid.org/0000-0001-7168-708X","contributorId":1538,"corporation":false,"usgs":true,"family":"Swain","given":"Eric","email":"edswain@usgs.gov","middleInitial":"D.","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":564858,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70155118,"text":"70155118 - 2015 - Influence of a chlor-alkali superfund site on mercury bioaccumulation in periphyton and low-trophic level fauna","interactions":[],"lastModifiedDate":"2018-09-04T15:42:28","indexId":"70155118","displayToPublicDate":"2015-07-29T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Influence of a chlor-alkali superfund site on mercury bioaccumulation in periphyton and low-trophic level fauna","docAbstract":"In Berlin, New Hampshire, USA, the Androscoggin River flows adjacent to a former chlor-alkali facility that is a US Environmental Protection Agency Superfund site and source of mercury (Hg) to the river. The present study was conducted to determine the fate and bioaccumulation of methylmercury (MeHg) to lower trophic-level taxa in the river. Surface sediment directly adjacent to the source showed significantly elevated MeHg (10–40× increase, mean ± standard deviation [SD]: 20.1 ± 24.8 ng g–1 dry wt) and total mercury (THg; 10–30× increase, mean ± SD: 2045 ± 2669 ng g–1 dry wt) compared with all other reaches, with sediment THg and MeHg from downstream reaches elevated (3–7× on average) relative to the reference (THg mean ± SD: 33.5 ± 9.33 ng g–1 dry wt; MeHg mean ± SD: 0.52 ± 0.21 ng g–1 dry wt). Water column THg concentrations adjacent to the point source for both particulate (0.23 ng L–1) and dissolved (0.76 ng L–1) fractions were 5-fold higher than at the reference sites, and 2-fold to 5-fold higher than downstream. Methylmercury production potential of periphyton material was highest (2–9 ng g–1 d–1 dry wt) adjacent to the Superfund site; other reaches were close to or below reporting limits (0. 1 ng g–1 d–1 dry wt). Total Hg and MeHg bioaccumulation in fauna was variable across sites and taxa, with no clear spatial patterns downstream of the contamination source. Crayfish, mayflies, and shiners showed a weak positive relationship with porewater MeHg concentration.
","language":"English","publisher":"Wiley","doi":"10.1002/etc.2964","usgsCitation":"Buckman, K., Marvin-DiPasquale, M.C., Taylor, V.F., Chalmers, A.T., Broadley, H.J., Agee, J.L., Jackson, B.P., and Chen, C.Y., 2015, Influence of a chlor-alkali superfund site on mercury bioaccumulation in periphyton and low-trophic level fauna: Environmental Toxicology and Chemistry, v. 34, no. 7, p. 1649-1658, https://doi.org/10.1002/etc.2964.","productDescription":"10 p.","startPage":"1649","endPage":"1658","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062266","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":471927,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4486627","text":"External Repository"},{"id":306246,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Hampshire","otherGeospatial":"Androscoggin River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.23741149902344,\n 44.38325649413712\n ],\n [\n -71.23741149902344,\n 44.62615246716885\n ],\n [\n -71.0760498046875,\n 44.62615246716885\n ],\n [\n -71.0760498046875,\n 44.38325649413712\n ],\n [\n -71.23741149902344,\n 44.38325649413712\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-02","publicationStatus":"PW","scienceBaseUri":"55b98fbbe4b08f6647be516f","contributors":{"authors":[{"text":"Buckman, Kate L.","contributorId":145628,"corporation":false,"usgs":false,"family":"Buckman","given":"Kate L.","affiliations":[{"id":16179,"text":"Dartmouth College, Hanover NH","active":true,"usgs":false}],"preferred":false,"id":564816,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marvin-DiPasquale, Mark C. 0000-0002-8186-9167 mmarvin@usgs.gov","orcid":"https://orcid.org/0000-0002-8186-9167","contributorId":1485,"corporation":false,"usgs":true,"family":"Marvin-DiPasquale","given":"Mark","email":"mmarvin@usgs.gov","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - 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In this study, species of monsoonal wetlands belonging to various functional types (graminoid and non−graminoid emergents, submersed aquatic, floating−leaved aquatic) varied in their growth responses to water depth and harvesting. We tested the effects of water depth (moist soil, flooded) and clipping (unclipped, and clipped) on the biomass and longevity of twenty−three dominant plant species of monsoonal wetlands in the Keoladeo National Park, India in a controlled experiment. With respect to total biomass and survival, six species responded positively to flooding and twelve species responded negatively to clipping. Responses to flooding and clipping, however, sometimes interacted. Individualistic responses of species to water levels and clipping regimes were apparent; species within a functional group did not always respond similarly. Therefore, detailed information on the individualistic responses of species may be needed to predict the vegetation composition of post−disturbance wetlands. In particular, as demands for fresh water increase around the world, studies of life history constraints and responses to hydrological changes will aid wetland managers in developing strategies to conserve biodiversity.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.aquabot.2015.06.004","usgsCitation":"Middleton, B.A., van der Valk, A., and Davis, C.B., 2015, Responses to water depth and clipping of twenty−three plant species in an Indian monsoonal wetland: Aquatic Botany, v. 126, p. 38-47, https://doi.org/10.1016/j.aquabot.2015.06.004.","productDescription":"10 p.","startPage":"38","endPage":"47","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055617","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":471928,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.aquabot.2015.06.004","text":"Publisher Index Page"},{"id":306214,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"India","otherGeospatial":"Keoladeo National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 77.57617950439453,\n 27.15050530215565\n ],\n [\n 77.50717163085936,\n 27.20517504065018\n ],\n [\n 77.48828887939453,\n 27.194487533747655\n ],\n [\n 77.48279571533203,\n 27.15783687748054\n ],\n [\n 77.53910064697266,\n 27.115368162224495\n ],\n [\n 77.57617950439453,\n 27.15050530215565\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"126","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55b899a0e4b09a3b01b6066d","contributors":{"authors":[{"text":"Middleton, Beth A. 0000-0002-1220-2326 middletonb@usgs.gov","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":2029,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","email":"middletonb@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":564770,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van der Valk, Arnold","contributorId":145612,"corporation":false,"usgs":false,"family":"van der Valk","given":"Arnold","affiliations":[{"id":15296,"text":"Iowa State University, Ames, IA, USA","active":true,"usgs":false}],"preferred":false,"id":564771,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davis, Craig B.","contributorId":145613,"corporation":false,"usgs":false,"family":"Davis","given":"Craig","email":"","middleInitial":"B.","affiliations":[{"id":16172,"text":"Ohio State University, Columbus, OH","active":true,"usgs":false}],"preferred":false,"id":564772,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70154961,"text":"70154961 - 2015 - Influence of hydrologic modifications on Fraxinus pennsylvanica in the Mississippi River Alluvial Valley, USA","interactions":[],"lastModifiedDate":"2015-09-28T11:01:38","indexId":"70154961","displayToPublicDate":"2015-07-22T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1170,"text":"Canadian Journal of Forest Research","active":true,"publicationSubtype":{"id":10}},"title":"Influence of hydrologic modifications on Fraxinus pennsylvanica in the Mississippi River Alluvial Valley, USA","docAbstract":"We used tree-ring analysis to examine radial growth response of a common, moderately flood-tolerant species (<i>Fraxinus pennsylvanica</i> Marshall) to hydrologic and climatic variability for > 40 years before and after hydrologic modifications affecting two forest stands in the Mississippi River Alluvial Valley (USA): a stand without levees below dams and a stand within a ring levee. At the stand without levees below dams, spring flood stages decreased and overall growth increased after dam construction, which we attribute to a reduction in flood stress. At the stand within a ring levee, growth responded to the elimination of overbank flooding by shifting from being positively correlated with river stage to not being correlated with river stage. In general, growth in swales was positively correlated with river stage and Palmer Drought Severity Index (an index of soil moisture) for longer periods than flats. Growth decreased after levee construction, but swales were less impacted than flats likely because of differences in elevation and soils provide higher soil moisture. Results of this study indicate that broad-scale hydrologic processes differ in their effects on the flood regime, and the effects on growth of moderately flood-tolerant species such as <i>F. pennsylvanica</i> can be mediated by local-scale factors such as topographic position, which affects soil moisture.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfr-2015-0138","usgsCitation":"Gee, H.K., King, S.L., and Keim, R., 2015, Influence of hydrologic modifications on Fraxinus pennsylvanica in the Mississippi River Alluvial Valley, USA: Canadian Journal of Forest Research, v. 45, no. 10, p. 1397-1406, https://doi.org/10.1139/cjfr-2015-0138.","productDescription":"10 p.","startPage":"1397","endPage":"1406","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-050730","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":305884,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Bayou Cocodrie National Wildlife Refuge, White River National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.834716796875,\n 31.31610138349565\n ],\n [\n -91.834716796875,\n 31.73050322928437\n ],\n [\n -91.38153076171875,\n 31.73050322928437\n ],\n [\n -91.38153076171875,\n 31.31610138349565\n ],\n [\n -91.834716796875,\n 31.31610138349565\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.56005859375,\n 33.568861182555565\n ],\n [\n -91.56005859375,\n 34.298068350990846\n ],\n [\n -90.8349609375,\n 34.298068350990846\n ],\n [\n -90.8349609375,\n 33.568861182555565\n ],\n [\n -91.56005859375,\n 33.568861182555565\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"10","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55b0b0a2e4b09a3b01b53070","contributors":{"authors":[{"text":"Gee, Hugo K.W.","contributorId":140925,"corporation":false,"usgs":false,"family":"Gee","given":"Hugo","email":"","middleInitial":"K.W.","affiliations":[],"preferred":false,"id":565293,"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":564412,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keim, Richard F.","contributorId":21858,"corporation":false,"usgs":true,"family":"Keim","given":"Richard F.","affiliations":[],"preferred":false,"id":565294,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70144993,"text":"sir20155036 - 2015 - Analysis of storm-tide impacts from Hurricane Sandy in New York","interactions":[],"lastModifiedDate":"2015-08-11T15:41:36","indexId":"sir20155036","displayToPublicDate":"2015-07-21T11:00:00","publicationYear":"2015","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":"2015-5036","title":"Analysis of storm-tide impacts from Hurricane Sandy in New York","docAbstract":"The hybrid cyclone-nor’easter known as Hurricane Sandy affected the mid-Atlantic and northeastern United States during October 28-30, 2012, causing extensive coastal flooding. Prior to storm landfall, the U.S. Geological Survey (USGS) deployed a temporary monitoring network from Virginia to Maine to record the storm tide and coastal flooding generated by Hurricane Sandy. This sensor network augmented USGS and National Oceanic and Atmospheric Administration (NOAA) networks of permanent monitoring sites that also documented storm surge. Continuous data from these networks were supplemented by an extensive post-storm high-water-mark (HWM) flagging and surveying campaign. The sensor deployment and HWM campaign were conducted under a directed mission assignment by the Federal Emergency Management Agency (FEMA). The need for hydrologic interpretation of monitoring data to assist in flood-damage analysis and future flood mitigation prompted the current analysis of Hurricane Sandy by the USGS under this FEMA mission assignment.
\nThe analysis of storm-tide impacts focused on three distinct but related aspects of coastal flooding from Hurricane Sandy, including flooding inland along the tidal reach of the Hudson River. These aspects are (1) comparisons of peak storm-tide elevations to those of historical storms and to annual exceedance probabilities, (2) assessments of storm-surge characteristics, and (3) comparisons of maps of inundation extent that were derived from differing amounts of available storm-tide data. Most peak storm-tide elevations from Hurricane Sandy were greater than about 9.5 feet (ft) above North American Vertical Datum of 1988.
\nPeak storm-tide elevations from Hurricane Sandy were compared with data for the intense nor’easter of December 11–13, 1992, and Hurricane Irene (August 27–28, 2011), which weakened to a tropical storm before arriving in New York. Peak storm-tide elevations from Hurricane Sandy were higher than those from the December 1992 nor’easter at 24 of 27 sites; most differences were greater than about 0.7 ft or 9 percent (above the historical storm tide). Peak storm-tide elevations from Hurricane Sandy were higher than those from Tropical Storm Irene at all sites; most differences were greater than about 2.5 ft or 48 percent. Data from permanent and temporary monitoring sites and HWM sites were compared with corresponding FEMA flood elevations for the 10-, 2-, 1-, and 0.2-percent annual exceedance probabilities in New York. Peak storm-tide elevations from Hurricane Sandy had annual exceedance probabilities less than or equal to 1 percent and (or) greater than 0.2 percent at a plurality of sites—184 of 413. Peak storm-tide elevations greater than or equal to the 0.2-percent flood elevation accounted for 81 of 413 sites. Peak storm-tide elevations less than the 10-percent flood elevation accounted for only 10 of 413 sites.
\nData from selected permanent monitoring sites in the USGS and NOAA networks were used to assess storm-surge magnitude associated with the peak storm tide, and magnitude and timing of the peak storm surge. Most magnitudes of the peak storm surge were greater than about 8.3 ft, and most magnitudes of the storm surge component of the peak storm tide were greater than about 7.8 ft. Timing of peak storm surge arrival with respect to local phase of tide controlled where the most extreme peak storm-tide levels and coastal flooding occurred. This finding has bearing not only for locations impacted by the highest storm tides from Hurricane Sandy, but also for those that had the greatest storm surges yet were spared the worst flooding because of fortuitous timing during this storm.
\nResults of FEMA Hazus Program (HAZUS) flood loss analyses performed for New York counties were compared for extents of storm-tide inundation from Hurricane Sandy mapped (1) pre-storm, (2) on November 11, 2012, and (3) on February 14, 2013. The resulting depictions of estimated total building stock losses document how differing amounts of available USGS data affect the resolution and accuracy of storm-tide inundation extents. Using the most accurate results from the final (February 14, 2013) inundation extent, estimated losses range from $380 million to $5.9 billion for individual New York counties; total estimated aggregate losses are about $23 billion for all New York counties. Quality of the inundation extents used in HAZUS analyses has a substantial effect on final results. These findings can be used to inform future post-storm reconstruction planning and estimation of insurance claims.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155036","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Schubert, C.E., Busciolano, Ronald, Hearn, P.P., Jr., Rahav, A.N., Behrens, Riley, Finkelstein, Jason, Monti, Jack, Jr., and Simonson, A.E., 2015, Analysis of storm-tide impacts from Hurricane Sandy in New York: U.S. Geological Survey Scientific Investigations Report 2015–5036, 75 p., https://dx.doi.org/10.3133/sir20155036.","productDescription":"iv, 75 p.","startPage":"1","endPage":"75","numberOfPages":"79","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052333","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":305838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5036/coverthb.jpg"},{"id":305840,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5036/sir20155036.pdf","text":"Report","size":"13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5036"},{"id":306207,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5036/sir20155036_printversion.pdf","text":"Report - Print Version","size":"19,468 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5036"}],"country":"United States","state":"New York","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.805908203125,\n 40.371658891506094\n ],\n [\n -74.805908203125,\n 42.827638636242284\n ],\n [\n -71.5869140625,\n 42.827638636242284\n ],\n [\n -71.5869140625,\n 40.371658891506094\n ],\n [\n -74.805908203125,\n 40.371658891506094\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
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Coram, NY 11727
http://ny.water.usgs.gov
Digital flood-inundation maps for a 6-mile reach of the Hohokus Brook in New Jersey from White's Lake Dam in Waldwick Borough, through Ho-Ho-Kus Borough to Grove Street in the Village of Ridgewood were created by the U.S. Geological Survey (USGS) in cooperation with the New Jersey Department of Environmental Protection. The flood inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the Hohokus Brook at Ho-Ho-Kus, New Jersey (station number 01391000). Stage data at this streamgage may be obtained on the Internet from the USGS National Water Information System at http://waterdata.usgs.gov/nwis/uv?site_no=01391000 or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at http://water.weather.gov/ahps2/hydrograph.php?gage=hohn4&wfo=okx.
\nFlood profiles were simulated for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated using the most current stage-discharge relation at the Hohokus Brook at Ho-Ho-Kus, New Jersey, streamgage (station number 01391000). The hydraulic model was then used to compute 12 water-surface profiles for flood stages at 0.5-foot (ft) intervals referenced to the streamgage datum and ranging from 2.5 ft, the NWS “action stage” or near bankfull, to 8.0 ft, which exceeds the stage that corresponds to the maximum recorded peak flow (7.32 ft) and is the extent of the current stage-discharge relation for the streamgage. The simulated water-surface profiles were then combined with a geographic information system 3-meter (9.84 ft) digital elevation model [derived from light detection and ranging (lidar) data] to delineate the area flooded at each water level.
\nThe availability of these maps along with information on the Internet regarding current stage from the USGS streamgage will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155064","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Watson, K.M., and Niemoczynski, M.J., 2015, Flood-Inundation maps for the Hohokus Brook in Waldwick Borough, Ho-Ho-Kus Borough, and the Village of Ridgewood, New Jersey, 2014: U.S. Geological Survey Scientific Investigations Report 2015–5064, 12 p., https://dx.doi.org/10.3133/sir20155064.","productDescription":"v, 12 p.","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-053102","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":305705,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5064/coverthb.jpg"},{"id":305706,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5064/sir20155064.pdf","text":"Report","size":"6.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5064"},{"id":305707,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2015/5064/downloads/depth_raster/","text":"Depth_Raster","size":"112 MB","description":"XML, ovr, adf, and Other Files"},{"id":305708,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2015/5064/downloads/KML/","text":"KML","size":"116 KB","description":"KMZ"},{"id":305709,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2015/5064/downloads/readme.txt","text":"Readme","size":"9.72 KB","linkFileType":{"id":2,"text":"txt"},"description":"Readme"},{"id":305710,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2015/5064/downloads/water_surface_final/","text":"Water Data","size":"1.43 MB","linkFileType":{"id":4,"text":"shapefile"},"description":"Water Surface"}],"country":"United States","state":"New Jersey","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.09042358398438,\n 40.86627605595889\n ],\n [\n -74.09042358398438,\n 40.914550362677204\n ],\n [\n -74.01592254638672,\n 40.914550362677204\n ],\n [\n -74.01592254638672,\n 40.86627605595889\n ],\n [\n -74.09042358398438,\n 40.86627605595889\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
http://nj.usgs.gov/
","tableOfContents":"
Stakeholders and water-resource managers in Lincoln County, New Mexico, have had long-standing concerns over the impact of population growth and groundwater withdrawals. These concerns have been exacerbated in recent years by extreme drought conditions and two major wildfires in the upper Rio Hondo Basin, located in south-central New Mexico. The U.S. Geological Survey (USGS), in cooperation with Lincoln County, initiated a study in 2006 to assess and characterize water resources in the upper Rio Hondo Basin. Data collected during water years 2010–13 are presented and interpreted in this report. All data presented in this report are described in water years unless stated otherwise.
\nAnnual mean streamflow at the Rio Ruidoso at Hollywood, N. Mex., streamflow-gaging station was less than 50 percent of the average streamflow during 2011–13 and was of similar magnitude to annual mean streamflow values measured during the drought of the 1950s. The first zero-streamflow values for the period of record (1954–2013) were recorded at the Rio Ruidoso at Hollywood, N. Mex., streamflow-gaging station on June 27–29, 2013. The lowest annual mean streamflow on record (1969–80; 1988–2013) occurred in 2011 at the Eagle Creek below South Fork near Alto, N. Mex., streamflow-gaging station, with the station recording zero streamflow for approximately 50 percent of the year.
\nDiscrete and continuous groundwater-level measurements indicated basinwide water-level declines during drought conditions in 2011–13. The average water-level change among 37 wells in which discrete groundwater-level measurements were collected was -7.6 ft from 2010 to 2013. The largest water-level declines were observed in the upper reaches of the Rio Bonito and Rio Ruidoso watersheds, and smaller declines were observed in the lower reaches of the watersheds. In general, water-level changes observed during 2010–13 were on the order of decadal-scale changes that previously have been observed in the upper Rio Hondo Basin.
\nStable-isotope data indicate that high-elevation winter precipitation generally contributes more to groundwater recharge than summer rains, except when there are large summer recharge events. This implies that little recharge is occurring at the lower elevations in the upper Rio Hondo Basin because these areas receive a smaller amount of total precipitation, receive a smaller proportion of the annual total falling as winter precipitation, and have higher average temperatures that result in more evaporative losses. Groundwater in the upper Rio Hondo Basin is a mix of younger and older water, and recharge likely is occurring primarily at higher elevations but there may be some areas where localized recharge is occurring at lower elevations.
\nSurface-water- and groundwater-quality results from samples collected in 2012–13 were examined to characterize overall chemistry and were compared to historical waterquality data from streams in the upper Rio Hondo Basin collected during 1926–57. In general, specific conductance showed an increasing trend moving eastward (downstream) through the upper Rio Hondo Basin in surface-water and groundwater samples. Surface-water and groundwater samples appear to have similar overall major-ion chemical characteristics when compared to historical water-quality data. Geology was found to influence the chemical characteristics of surface-water and groundwater samples, with relatively higher concentrations of sulfate occurring in samples collected at lower elevations in the Permian regional aquifer system.
\nSurface-water sample results also were analyzed to determine differences in unfiltered and filtered water-quality samples of streams in burned and unburned watersheds after the occurrence of the Little Bear Fire in June 2012. Samples were collected after postfire monsoon rain events and during periods of stable hydrologic conditions. The first postfire monsoon rain event in July 2012 generally produced the highest measured concentrations of selected fire-related constituents in unfiltered samples collected in the burned watersheds relative to later samples collected in burned watersheds and all samples collected in the unburned watershed. Monsoon rain events have impacted water quality by delivering larger sediment loads and fire-related constituents into streams in the upper Rio Hondo Basin.
\nChanges in climate and increased groundwater and surface-water use are likely to affect the availability of water in the upper Rio Hondo Basin. Increased drought probably will increase the potential for wildfires, which can affect downstream water quality and increase flood potential. Climate-research predicted decreases in winter precipitation may have an adverse effect on the amount of groundwater recharge that occurs in the upper Rio Hondo Basin, given the predominance of winter precipitation recharge as indicated by the stable isotope results. Decreases in surface-water supplies because of persistent drought conditions and reductions in the quality of water because of the effects of wildfire may lead to a larger reliance on groundwater reserves in the upper Rio Hondo Basin. Decreasing water levels because of increasing groundwater withdrawal could reduce base flows in the Rio Bonito and Rio Ruidoso. Well organized and scientifically supported regional water-resources management will be necessary for dealing with the likely scenario of increases in demand coupled with decreases in supply in the upper Rio Hondo Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155086","collaboration":"Prepared in cooperation with Lincoln County, New Mexico","usgsCitation":"Sherson, L.R. and Rice, S.E., 2015, Water resources during drought conditions and postfire water quality in the upper Rio Hondo Basin, Lincoln County, New Mexico, 2010–13: U.S. Geological Survey Scientific Investigations Report 2015–5086, 56 p., https://dx.doi.org/10.3133/sir20155086.","productDescription":"vii, 56 p.","numberOfPages":"67","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-058239","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":305800,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5086/coverthb.jpg"},{"id":305801,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5086/sir20155086.pdf","text":"Report","size":"5.79 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5086"}],"country":"United States","state":"New Mexico","county":"Lincoln County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.20208740234375,\n 33.40163829558248\n ],\n [\n -106.20208740234375,\n 34.31394984163214\n ],\n [\n -104.70794677734374,\n 34.31394984163214\n ],\n [\n -104.70794677734374,\n 33.40163829558248\n ],\n [\n -106.20208740234375,\n 33.40163829558248\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
5338 Montgomery Blvd NE, Suite 400
Albuquerque, NM 87109
http://nm.water.usgs.gov/
Lacustrine groundwater discharge (LGD) transports nutrients from a catchment to a lake, which may fuel eutrophication, one of the major threats to our fresh waters. Unfortunately, LGD has often been disregarded in lake nutrient studies. Most measurement techniques are based on separate determinations of volume and nutrient concentration of LGD: Loads are calculated by multiplying seepage volumes by concentrations of exfiltrating water. Typically low phosphorus (P) concentrations of pristine groundwater often are increased due to anthropogenic sources such as fertilizer, manure or sewage. Mineralization of naturally present organic matter might also increase groundwater P. Reducing redox conditions favour P transport through the aquifer to the reactive aquifer-lake interface. In some cases, large decreases of P concentrations may occur at the interface, for example, due to increased oxygen availability, while in other cases, there is nearly no decrease in P. The high reactivity of the interface complicates quantification of groundwater-borne P loads to the lake, making difficult clear differentiation of internal and external P loads to surface water. Anthropogenic sources of nitrogen (N) in groundwater are similar to those of phosphate. However, the environmental fate of N differs fundamentally from P because N occurs in several different redox states, each with different mobility. While nitrate behaves essentially conservatively in most oxic aquifers, ammonium's mobility is similar to that of phosphate. Nitrate may be transformed to gaseous N2 in reducing conditions and permanently removed from the system. Biogeochemical turnover of N is common at the reactive aquifer-lake interface. Nutrient loads from LGD were compiled from the literature. Groundwater-borne P loads vary from 0.74 to 2900 mg PO4-P m−2 year−1; for N, these loads vary from 0.001 to 640 g m−2 year−1. Even small amounts of seepage can carry large nutrient loads due to often high nutrient concentrations in groundwater. Large spatial heterogeneity, uncertain areal extent of the interface and difficult accessibility make every determination of LGD a challenge. However, determinations of LGD are essential to effective lake management.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.10384","usgsCitation":"Lewandowski, J., Meinikmann, K., Nutzmann, G., and Rosenberry, D.O., 2015, Groundwater – The disregarded component in lake water and nutrient budgets. Part 2: effects of groundwater on nutrients: Hydrological Processes, v. 29, no. 13, p. 2922-2955, https://doi.org/10.1002/hyp.10384.","productDescription":"34 p.","startPage":"2922","endPage":"2955","ipdsId":"IP-053820","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":344564,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"13","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-27","publicationStatus":"PW","scienceBaseUri":"5984364ae4b0e2f5d46653cd","contributors":{"authors":[{"text":"Lewandowski, Jorg","contributorId":195317,"corporation":false,"usgs":false,"family":"Lewandowski","given":"Jorg","email":"","affiliations":[],"preferred":false,"id":706749,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meinikmann, Karin","contributorId":195318,"corporation":false,"usgs":false,"family":"Meinikmann","given":"Karin","email":"","affiliations":[],"preferred":false,"id":706750,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nutzmann, Gunnar","contributorId":195319,"corporation":false,"usgs":false,"family":"Nutzmann","given":"Gunnar","email":"","affiliations":[],"preferred":false,"id":706751,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":706748,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70148009,"text":"ofr20151095 - 2015 - Design and methods of the Southeast Stream Quality Assessment (SESQA), 2014","interactions":[],"lastModifiedDate":"2019-04-11T15:33:59","indexId":"ofr20151095","displayToPublicDate":"2015-07-15T10:45:00","publicationYear":"2015","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":"2015-1095","title":"Design and methods of the Southeast Stream Quality Assessment (SESQA), 2014","docAbstract":"During 2014, the U.S. Geological Survey (USGS) National Water-Quality Assessment Program (NAWQA) assessed stream quality across the Piedmont and southern Appalachian Mountain regions of the southeastern United States. This Southeast Stream Quality Assessment (SESQA) simultaneously characterized watershed and stream-reach water-quality stressors along with instream biological conditions, in order to better understand regional stressor-effects relations. The goal of SESQA is to provide communities and policymakers with information about those human and environmental factors that have the greatest impact on stream quality across the region. The SESQA design focused on hydrologic alteration and urbanization because of their importance as ecological stressors of particular concern to Southeast region resource managers.
\nStreamflow and land-use data were used to identify and select sites representing gradients in urbanization and streamflow alteration across the region. One hundred fifteen sites were selected and sampled for as many as 10 weeks during April, May, and June 2014 for contaminants, nutrients, and sediment. This water-quality “index” period culminated with an ecological survey of habitat, periphyton, benthic macroinvertebrates, and fish at all sites. Sediment was collected during the ecological survey for analysis of sediment chemistry and toxicity testing. Of the 115 sites, 59 were on streams in watersheds with varying degrees of urban land use, 5 were on streams with multiple confined animal feeding operations, and 13 were reference sites with little or no development in their watersheds. The remaining 38 “hydro” sites were on streams in watersheds with relatively little agricultural or urban development but with hydrologic alteration, such as a dam or reservoir.
\nThis report provides a detailed description of the SESQA study components, including surveys of ecological conditions, routine water sampling, deployment of passive polar organic compound integrative samplers for pesticides and contaminants of emerging concern, and synoptic sediment sampling and toxicity testing at all urban, confined animal feeding operation, and reference sites. Continuous water-quality monitoring and daily pesticide sampling efforts conducted at a subset of urban sites are also described.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151095","collaboration":"Prepared in cooperation with the National Water-Quality Assessment Program","usgsCitation":"Journey, C.A., Van Metre, P.C., Bell, A.H., Garrett, J.D., Button, D.T., Nakagaki, N., Qi, S.L., and Bradley, P.M., 2015, Design and methods of the Southeast Stream Quality Assessment (SESQA), 2014: U.S. Geological Survey Open-File Report 2015–1095, 46 p., https://dx.doi.org/10.3133/ofr20151095.","productDescription":"Report: vii, 46 p.; 3 Appendices","numberOfPages":"58","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-063365","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":305724,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1095/ofr20151095_appendix2.xlsx","text":"Appendix 2","size":"89 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Description of the U.S. Geological Survey National Water Quality Laboratory Schedules Used for Water, Sediment, and Periphyton"},{"id":305722,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1095/ofr20151095.pdf","text":"Report","size":"3.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1095"},{"id":305723,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1095/ofr20151095_appendix1.xlsx","text":"Appendix 1","size":"560 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Description of the Sampling Timelines, Matrix, Collection, and Processing for Water, Sediment, and Ecological Samples"},{"id":305725,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1095/ofr20151095_appendix3.xlsx","text":"Appendix 3","size":"50 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Counts of Environmental (Environ), Field Blank, Replicate (Rep), and Spike Samples of Streamwater by Site and Laboratory Analysis From the 115 Stream Sites Sampled in the U.S. Geological Survey (USGS) Southeastern Stream Quality Assessment (SESQA) Study in 2014"},{"id":305721,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1095/coverthb.jpg"}],"country":"United States","state":"Alabama, Georgia, North Carolina, South Carolina, Tennessee, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.51953125,\n 39.13006024213511\n ],\n [\n -77.89306640625,\n 38.788345355085625\n ],\n [\n -77.1240234375,\n 38.976492485539424\n ],\n [\n -76.79443359375,\n 38.788345355085625\n ],\n [\n -77.431640625,\n 38.22091976683121\n ],\n [\n -77.27783203125,\n 37.85750715625203\n ],\n [\n -77.05810546875,\n 37.23032838760387\n ],\n [\n -77.34374999999999,\n 36.54494944148322\n ],\n [\n -77.58544921874999,\n 36.049098959065645\n ],\n [\n -78.64013671875,\n 35.35321610123821\n ],\n [\n -79.40917968749999,\n 35.22767235493586\n ],\n [\n -79.89257812499999,\n 34.77771580360469\n ],\n [\n -80.2001953125,\n 34.43409789359469\n ],\n [\n -80.7275390625,\n 34.08906131584996\n ],\n [\n -81.27685546875,\n 33.50475906922606\n ],\n [\n -81.80419921875,\n 33.211116472416855\n ],\n [\n -83.1884765625,\n 32.80574473290688\n ],\n [\n -84.66064453125,\n 32.379961464357315\n ],\n [\n -85.078125,\n 32.287132632616355\n ],\n [\n -86.572265625,\n 32.24997445586331\n ],\n [\n -87.3193359375,\n 32.602361666817515\n ],\n [\n -86.90185546874999,\n 33.358061612778876\n ],\n [\n -86.2646484375,\n 34.14363482031264\n ],\n [\n -85.58349609375,\n 34.92197103616377\n ],\n [\n -83.82568359375,\n 36.58024660149866\n ],\n [\n -81.4306640625,\n 37.35269280367274\n ],\n [\n -80.39794921875,\n 37.77071473849609\n ],\n [\n -79.7607421875,\n 38.65119833229951\n ],\n [\n -79.38720703125,\n 38.685509760012\n ],\n [\n -78.7060546875,\n 39.21523130910493\n ],\n [\n -78.3544921875,\n 39.53793974517628\n ],\n [\n -77.51953125,\n 39.13006024213511\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
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720 Gracern Road, Suite 129
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
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Hydrologic data and conditions throughout Rhode Island during water year 2014 are presented in this report. Stream discharge and groundwater level conditions varied geographically across the State. Ten streamgages reached record-low minimum monthly mean discharges during the year, and a record-high maximum groundwater level was observed at one groundwater well.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151127","usgsCitation":"Verdi, R.J., and Socolow, R.S., 2015, Hydrologic conditions in Rhode Island during water year 2014: U.S. Geological Survey Open-File Report 2015–1127, 8 p., https://dx.doi.org/10.3133/ofr20151127.","productDescription":"iv, 8 p.","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065518","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":305738,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1127/coverthb.jpg"},{"id":305739,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1127/ofr20151127.pdf","text":"Report","size":"875 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1127"}],"country":"United States","state":"Rhode 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Island\",\"nation\":\"USA \"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
http://ma.water.usgs.gov
http://ri.water.usgs.gov