This study examined links among fluvial, aeolian, and hillslope geomorphic processes that affect archeological sites and surrounding landscapes in the Colorado River corridor downstream from Glen Canyon Dam, Arizona. We assessed the potential for Colorado River sediment to enhance the preservation of river-corridor archeological resources through aeolian sand deposition or mitigation of gully erosion. By identifying locally prevailing wind directions, locations of modern sandbars, and likely aeolian-transport barriers, we determined that relatively few archeological sites are now ideally situated to receive aeolian sand supply from sandbars deposited by recent controlled floods. Whereas three-fourths of the 358 river-corridor archeological sites we examined include Colorado River sediment as an integral component of their geomorphic context, only 32 sites currently appear to have a high degree of connectivity (coupled interactions) between modern fluvial sandbars and sand-dominated landscapes downwind. This represents a substantial decrease from past decades, as determined by aerial-photograph analysis. Thus, we infer that recent controlled floods have had a limited, and declining, influence on archeological-site preservation.
\nWithin the study area, overland-flow (gully) erosion is less severe in sand landscapes with active aeolian sand than in landscapes that lack aeolian transport; gullies terminate more commonly in active sand (sand that is mobile by wind rather than stabilized by biologic soil crust). We infer that these characteristics largely result from aeolian sand transport being an effective gully-limiting and gully-annealing mechanism. Aeolian sand activity in the river corridor varies substantially as a function of reach morphology and dominant wind direction relative to the river-corridor orientation, factors that control accommodation space for river-derived sand and the modern sand supply to aeolian dunes. These attributes, together with an inverse correlation between aeolian sand activity and gully occurrence, define varying degrees of net long-term gully-erosion risk for sediment deposits and associated archeological sites in different regions of the river corridor. Over most of the river corridor, including some of the archeologically richest regions, sand is too inactive with respect to aeolian transport to anneal gullies effectively. At eight selected archeological sites that we studied with high-resolution terrestrial lidar scans for more than a year, sand loss by overland flow (gully erosion) and aeolian deflation generally exceeded deposition, such that erosion dominated over most monitoring intervals—even at four sites with strong connectivity to modern sand supply.
\nThe Glen Canyon reach of the river corridor appears especially vulnerable to gully erosion. Among the sites that we monitored in detail, erosion generally dominated over deposition to a greater degree at four Glen Canyon sites with no modern sand supply than at four Marble–Grand Canyon sites with aeolian sand supply from controlled-flood sandbars. Although gross annual-scale erosion rates were similar among the Glen Canyon sites and among the Marble–Grand Canyon sites, a relative lack of depositional processes led to greater net erosion at the Glen Canyon sites. Having found no differences in weather patterns to suggest greater erosive forcing in Glen Canyon, and no conclusively influential differences in the slope or watershed area contributing to gully formation, we attribute the greater erosion at the Glen Canyon sites to a combination of inherent geomorphic context (high terraces that do not receive modern sediment supply) and pronounced effects of postdam sediment-supply limitation.
\nWe conclude that most of the river-corridor archeological sites are at elevated risk of net erosion under present dam operations. In the present flow regime, controlled floods do not simulate the magnitude or frequency of natural floods, and are not large enough to deposit sand at elevations that were flooded at annual to decadal intervals in predam time. For archeological sites that depend upon river-derived sand, we infer elevated erosion risk owing to a combination of reduced sand supply (both fluvial and aeolian) through (1) the lower-than-natural flood magnitude, frequency, and sediment supply of the controlled-flooding protocol; (2) reduction of open, dry sand area available for wind redistribution under current normal (nonflood) dam operations, which do not include flows as low as natural seasonal low flows and do include substantial daily flow fluctuations; and (3) impeded aeolian sand entrainment and transport owing to increased riparian vegetation growth in the absence of larger, more-frequent floods. If dam operations were to increase the supply of sand available for windblown transport—for example, through larger floods, sediment augmentation, or increased fluvial sandbar exposure by low flows—and also decrease riparian vegetation, the prevalence of active aeolian sand could increase over time, and the propensity for unmitigated gully erosion could decrease. Although the evolution of river-corridor landscapes and archeological sites has been altered fundamentally by the lack of large, sediment-rich floods (flows on the order of 5,000 m3/s), some combination of sediment-rich flows above 1,270 m3/s, seasonal flows below 226 m3/s, and riparian-vegetation removal might increase the preservation potential for sand-dependent archeological resources in the Colorado River corridor.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1825","usgsCitation":"East, A.E., Collins, B.D., Sankey, J.B., Corbett, S.C., Fairley, H.C., and Caster, J., 2016, Conditions and processes affecting sand resources at archeological sites in the Colorado River corridor below Glen Canyon Dam, Arizona: U.S. Geological Survey Professional Paper 1825, 104 p., https://dx.doi.org/10.3133/pp1825.","productDescription":"ix, 104 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066266","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":321261,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1825/coverthb.jpg"},{"id":321262,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1825/pp1825.pdf","text":"Report","size":"30.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP1825"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River corridor","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.555,\n 37.05\n ],\n [\n -114.555,\n 35.45\n ],\n [\n -110.75,\n 35.45\n ],\n [\n -110.75,\n 37.05\n ],\n [\n -114.555,\n 37.05\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"SBSC Staff, Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
http://sbsc.wr.usgs.gov/
The original National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL) was extensively modified to increase the spatial sampling density and to improve performance in water ranging from 3 to 44 meters (m). The new (EAARL-B) sensor features a higher spatial density that was achieved by optically splitting each laser pulse into three pulses spatially separated by 1.6 m along the flight track and 2.0 m across the flight track, on the water surface when flown at a nominal altitude of 300 m (984 feet). The sample spacing can be optionally increased to 1.0 m across the flight track. Improved depth capability was achieved by increasing the total peak laser power by a factor of 10 and by designing a new “deep-water” receiver, which is optimized to exclusively receive refracted and scattered light from deeper water (15–44 m).
\nTwo different clear-water flight missions were conducted over the U.S. Navy's South Florida Testing Facility (SFTF) to determine the EAARL-B calibration coefficients. The SFTF is an established lidar calibration range located in the coastal waters southeast of Fort Lauderdale, Florida. We used 23 selected polygons at 23 distinct depths to compare a reference dataset from this site to determine EAARL-B calibration constants over the depth range of 6.5 to 34 m.
\nWe also conducted a near-simultaneous single-beam jet-ski-based sonar survey of selected transects ranging from 1 to 33 m depth in the same area. The near-concurrent jet ski data were used to evaluate the EAARL-B performance over the depth range from 0.9 to 10 m. The more timely jet ski data were necessary because the primary reference dataset was 9 years old, and areas shallower than 6.5 m are dominated by shifting sand. We determined the jet ski data were not useful as a calibration reference in water deeper than 10 m due to large uncertainty in the vertical measurement introduced by the lack of any sensor orientation data, that is, for pitch, roll, and heading to correct the measured slant range to a vertical measurement.
\nThe resulting calibrated EAARL-B data were then analyzed and compared with the original reference dataset, the jet-ski-based dataset from the same Fort Lauderdale site, as well as the depth-accuracy requirements of the International Hydrographic Organization (IHO). We do not claim to meet all of the IHO requirements and standards. The IHO minimum depth-accuracy requirements were used as a reference only and we do not address the other IHO requirements such as “ Full Seafloor Search”. Our results show good agreement between the calibrated EAARL-B data and all reference datasets, with results that are within the 95 percent depth accuracy of the IHO Order 1 (a and b) depth-accuracy requirements.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161048","usgsCitation":"Wright, C.W., Kranenburg, C.J., Troche, R.J., Mitchell, R.W., and, Nagle, D.B., 2016, Depth calibration of the experimental advanced airborne research lidar, EAARL-B: U.S. Geological Survey Open-File Report 2016–1048, 23 p., https://dx.doi.org/10.3133/ofr20161048.","productDescription":"Report: vi, 22 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-061552","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":320937,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1048/coverthb.jpg"},{"id":320951,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://dx.doi.org/10.5066/F79S1P4S","text":"Data Release"},{"id":320938,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1048/ofr20161048.pdf","text":"Report","size":"1.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1048"}],"contact":"Director, St. Petersburg Coastal and Marine Science Center
600 4th Street South
St. Petersburg, FL 33701
(727) 502-8000
http://coastal.er.usgs.gov/
Rates of oxygen and nitrate reduction are key factors in determining the chemical evolution of groundwater. Little is known about how these rates vary and covary in regional groundwater settings, as few studies have focused on regional datasets with multiple tracers and methods of analysis that account for effects of mixed residence times on apparent reaction rates. This study provides insight into the characteristics of residence times and rates of O2 reduction and denitrification (NO3− reduction) by comparing reaction rates using multi-model analytical residence time distributions (RTDs) applied to a data set of atmospheric tracers of groundwater age and geochemical data from 141 well samples in the Central Eastern San Joaquin Valley, CA. The RTD approach accounts for mixtures of residence times in a single sample to provide estimates of in-situ rates. Tracers included SF6, CFCs, 3H, He from 3H (tritiogenic He),14C, and terrigenic He. Parameter estimation and multi-model averaging were used to establish RTDs with lower error variances than those produced by individual RTD models. The set of multi-model RTDs was used in combination with NO3− and dissolved gas data to estimate zero order and first order rates of O2 reduction and denitrification. Results indicated that O2 reduction and denitrification rates followed approximately log-normal distributions. Rates of O2 and NO3− reduction were correlated and, on an electron milliequivalent basis, denitrification rates tended to exceed O2 reduction rates. Estimated historical NO3− trends were similar to historical measurements. Results show that the multi-model approach can improve estimation of age distributions, and that relatively easily measured O2 rates can provide information about trends in denitrification rates, which are more difficult to estimate.
","language":"English","publisher":"European Geophysical Society","doi":"10.1016/j.jhydrol.2016.05.018","usgsCitation":"Green, C.T., Jurgens, B.C., Zhang, Y., Starn, J., Singleton, M.J., and Esser, B.K., 2016, Regional oxygen reduction and denitrification rates in groundwater from multi-model residence time distributions, San Joaquin Valley, USA: Journal of Hydrology, v. 145, p. 47-55, https://doi.org/10.1016/j.jhydrol.2016.05.018.","productDescription":"9 p.","startPage":"47","endPage":"55","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067486","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"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":470992,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2016.05.018","text":"Publisher Index Page"},{"id":321295,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.5,\n 37\n ],\n [\n -121.5,\n 38\n ],\n [\n -120,\n 38\n ],\n [\n -120,\n 37\n ],\n [\n -121.5,\n 37\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"145","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"574d566fe4b07e28b667f7a0","contributors":{"authors":[{"text":"Green, Christopher T. 0000-0002-6480-8194 ctgreen@usgs.gov","orcid":"https://orcid.org/0000-0002-6480-8194","contributorId":1343,"corporation":false,"usgs":true,"family":"Green","given":"Christopher","email":"ctgreen@usgs.gov","middleInitial":"T.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":629354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X bjurgens@usgs.gov","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":127842,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","email":"bjurgens@usgs.gov","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Yong","contributorId":19029,"corporation":false,"usgs":true,"family":"Zhang","given":"Yong","affiliations":[],"preferred":false,"id":629356,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Starn, Jeffrey jjstarn@usgs.gov","contributorId":149231,"corporation":false,"usgs":true,"family":"Starn","given":"Jeffrey","email":"jjstarn@usgs.gov","affiliations":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629357,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Singleton, Michael J.","contributorId":44400,"corporation":false,"usgs":true,"family":"Singleton","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":629358,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Esser, Bradley K.","contributorId":33161,"corporation":false,"usgs":true,"family":"Esser","given":"Bradley","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":629359,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70176544,"text":"70176544 - 2016 - Freshwater wrack along Great Lakes coasts harbors Escherichia coli: Potential for bacterial transfer between watershed environments","interactions":[],"lastModifiedDate":"2021-08-24T15:41:50.623597","indexId":"70176544","displayToPublicDate":"2016-05-17T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Freshwater wrack along Great Lakes coasts harbors Escherichia coli: Potential for bacterial transfer between watershed environments","title":"Freshwater wrack along Great Lakes coasts harbors Escherichia coli: Potential for bacterial transfer between watershed environments","docAbstract":"We investigated the occurrence, persistence, and growth potential of Escherichia coli associated with freshwater organic debris (i.e., wrack) frequently deposited along shorelines (shoreline wrack), inputs from rivers (river CPOM), and parking lot runoffs (urban litter). Samples were collected from 9 Great Lakes beaches, 3 creeks, and 4 beach parking lots. Shoreline wrack samples were mainly composed of wood chips, straw, sticks, leaf litter, seeds, feathers, and mussel shells; creek and parking lot samples included dry grass, straw, seeds, wood chips, leaf/pine needle litter; soil particles were present in parking lot samples only. E. coli concentrations (most probable number, MPN) were highly variable in all sample types: shoreline wrack frequently reached 105/g dry weight (dw), river CPOM ranged from 81 to 7,916/g dw, and urban litter ranged from 0.5 to 24,952/g dw. Sequential rinsing studies showed that 61–87% of E. coli concentrations were detected in the first wash of shoreline wrack, with declining concentrations associated with 4–8 subsequent washings; viable counts were still detected even after 8 washes. E. coli grew readily in shoreline wrack and river CPOM incubated at 35 °C. At 30°C, growth was only detected in river CPOM and not in shoreline wrack or urban litter, but the bacteria persisted for at least 16 days. In summary, freshwater wrack is an understudied component of the beach ecosystem that harbors E. coli and thus likely influences estimations of water quality and the microbial community in the nearshore as a result of transfer between environments.
","language":"English","publisher":"International Association for Great Lakes Research","doi":"10.1016/j.jglr.2016.04.011","usgsCitation":"Nevers, M., Przybyla-Kelly, K., Spoljaric, A., Shively, D.A., Whitman, R.L., and Byappanahalli, M., 2016, Freshwater wrack along Great Lakes coasts harbors Escherichia coli: Potential for bacterial transfer between watershed environments: Journal of Great Lakes Research, v. 42, no. 4, p. 760-767, https://doi.org/10.1016/j.jglr.2016.04.011.","productDescription":"8 p.","startPage":"760","endPage":"767","ipdsId":"IP-071134","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":328805,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Illinois, Indiana, Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": 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-87.64892578125,\n 41.61338889474735\n ],\n [\n -87.72857666015624,\n 41.72828028223453\n ],\n [\n -87.769775390625,\n 41.99828401778616\n ],\n [\n -87.7587890625,\n 42.037054301883806\n ],\n [\n -87.703857421875,\n 42.05337156043361\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.771240234375,\n 43.63408731864001\n ],\n [\n -81.771240234375,\n 43.82065657651688\n ],\n [\n -81.63665771484375,\n 43.82065657651688\n ],\n [\n -81.63665771484375,\n 43.63408731864001\n ],\n [\n -81.771240234375,\n 43.63408731864001\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7c6bbe4b0bc0bec09cb0c","contributors":{"authors":[{"text":"Nevers, Meredith 0000-0001-6963-6734 mnevers@usgs.gov","orcid":"https://orcid.org/0000-0001-6963-6734","contributorId":2013,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith","email":"mnevers@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":649164,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Przybyla-Kelly, Kasia","contributorId":79004,"corporation":false,"usgs":true,"family":"Przybyla-Kelly","given":"Kasia","affiliations":[],"preferred":false,"id":649180,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spoljaric, Ashley 0000-0001-6262-030X aspoljaric@usgs.gov","orcid":"https://orcid.org/0000-0001-6262-030X","contributorId":139464,"corporation":false,"usgs":true,"family":"Spoljaric","given":"Ashley","email":"aspoljaric@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":649166,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shively, Dawn A. dshively@usgs.gov","contributorId":2051,"corporation":false,"usgs":true,"family":"Shively","given":"Dawn","email":"dshively@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":649167,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Whitman, Richard L. rwhitman@usgs.gov","contributorId":542,"corporation":false,"usgs":true,"family":"Whitman","given":"Richard","email":"rwhitman@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":649168,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Byappanahalli, Muruleedhara 0000-0001-5376-597X byappan@usgs.gov","orcid":"https://orcid.org/0000-0001-5376-597X","contributorId":147923,"corporation":false,"usgs":true,"family":"Byappanahalli","given":"Muruleedhara","email":"byappan@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":649169,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70169143,"text":"sir20165033 - 2016 - Effects of variations in flow characteristics through W.P. Franklin Lock and Dam on downstream water quality in the Caloosahatchee River Estuary and in McIntyre Creek in the J.N. “Ding” Darling National Wildlife Refuge, southern Florida, 2010–13","interactions":[],"lastModifiedDate":"2016-05-18T08:50:38","indexId":"sir20165033","displayToPublicDate":"2016-05-17T00:00:00","publicationYear":"2016","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":"2016-5033","title":"Effects of variations in flow characteristics through W.P. Franklin Lock and Dam on downstream water quality in the Caloosahatchee River Estuary and in McIntyre Creek in the J.N. “Ding” Darling National Wildlife Refuge, southern Florida, 2010–13","docAbstract":"The U.S. Geological Survey studied water-quality trends at the mouth of McIntyre Creek, an entry point to the J.N. “Ding” Darling National Wildlife Refuge, to investigate correlations between flow rates and volumes through the W.P. Franklin Lock and Dam and water-quality constituents inside the refuge from March 2010 to December 2013. Outflow from Lake Okeechobee, and flows from Franklin Lock, tributaries to the Caloosahatchee River Estuary, and the Cape Coral canal system were examined to determine the sources and quantity of water to the study area. Salinity, temperature, dissolved-oxygen concentration, pH, turbidity, and chromophoric dissolved organic matter fluorescence (FDOM) were measured during moving-boat surveys and at a fixed location in McIntyre Creek. Chlorophyll fluorescence was also recorded in McIntyre Creek. Water-quality surveys were completed on 20 dates between 2011 and 2014 using moving-boat surveys.
Franklin Lock contributed the majority of flow to the Caloosahatchee River. Between 2010 and 2013, the monthly mean flow rate at Franklin Lock ranged from 29 cubic feet per second in May 2011 to 10,650 cubic feet per second in August 2013. Instantaneous near-surface salinity in McIntyre Creek ranged from 12.9 parts per thousand on September 26, 2013, to 37.9 parts per thousand on June 27, 2011. Salinity in McIntyre Creek decreased with increasing flow rate through Franklin Lock. Flow rates through Franklin Lock explained 61 percent of the variation in salinity in McIntyre Creek. Salinity data from moving-boat surveys also indicate that an increase in flow rate at Franklin Lock decreases salinity in the Caloosahatchee River Estuary, and a reduction or elimination in flow increases salinity. The FDOM in McIntyre Creek was positively correlated with flow at Franklin Lock, and 54 percent of the variation in FDOM can be attributed to the flow rate through Franklin Lock. Data from moving-boat surveys indicate that FDOM increases when flow volume from Franklin Lock increases. The highest FDOM recorded during a survey was at Billy’s Creek. Chlorophyll fluorescence was positively correlated with flow at Franklin Lock, with 23 percent of the variation explained by the flow rate at Franklin Lock. An increase in flow rate at Franklin Lock resulted in a decrease in pH (21 percent of variation explained by flow rates). Data from the pH surveys indicate an increase in pH with distance from Franklin Lock. Turbidity and dissolved oxygen near the surface in McIntyre Creek were not correlated with flow rate at Franklin Lock. Moving-boat surveys did not document a change in turbidity or dissolved oxygen with a change in distance from the Franklin Lock. Correlations between Franklin Lock flow rate and water quality in McIntyre Creek indicate that releases at Franklin Lock affect water quality in the Caloosahatchee River Estuary and Ding Darling Refuge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165033","collaboration":"Prepared as part of the Greater Everglades Priority Ecosystems Science Initiative and in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Booth, A.C., Soderqvist, L.E., and Knight, T.M., 2016, Effects of variations in flow characteristics through W.P. Franklin Lock and Dam on downstream water quality in the Caloosahatchee River Estuary and in McIntyre Creek in the J.N. “Ding” Darling National Wildlife Refuge, southern Florida, 2010–13: U.S. Geological Survey Scientific Investigations Report 2016–5033, 33 p., https://dx.doi.org/10.3133/sir20165033.","productDescription":"Report: vii, 33 p.; Data Release","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063026","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"links":[{"id":321251,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5033/coverthb.jpg"},{"id":321252,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5033/sir20165033.pdf","text":"Report","size":"11.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5033"},{"id":321253,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://dx.doi.org/10.5066/F70863BC","text":"Data Release","description":"Data Release"}],"country":"United States","state":"Florida","otherGeospatial":"Caloosahatchee River Estuary, J.N. “Ding” Darling National Wildlife Refuge, McIntyre Creek,","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.1942138671875,\n 26.40417061185344\n ],\n [\n -82.1942138671875,\n 26.831423660953195\n ],\n [\n -81.24938964843749,\n 26.831423660953195\n ],\n [\n -81.24938964843749,\n 26.40417061185344\n ],\n [\n -82.1942138671875,\n 26.40417061185344\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Biogenic coalbed methane (CBM), a microbially-generated source of natural gas trapped within coal beds, is an important energy resource in many countries. Specific bacterial populations and enzymes involved in coal degradation, the potential rate-limiting step of CBM formation, are relatively unknown. The U.S. Geological Survey (USGS) has established a field site, (Birney test site), in an undeveloped area of the Powder River Basin (PRB), with four wells completed in the Flowers-Goodale coal bed, one in the overlying sandstone formation, and four in overlying and underlying coal beds (Knoblach, Nance, and Terret). The nine wells were positioned to characterize the hydraulic conductivity of the Flowers-Goodale coal bed and were selectively cored to investigate the hydrogeochemistry and microbiology associated with CBM production at the Birney test site. Aquifer-test results indicated the Flowers-Goodale coal bed, in a zone from about 112 to 120 m below land surface at the test site, had very low hydraulic conductivity (0.005 m/d) compared to other PRB coal beds examined. Consistent with microbial methanogenesis, groundwater in the coal bed and overlying sandstone contain dissolved methane (46 mg/L average) with low δ13C values (−67‰ average), high alkalinity values (22 meq/kg average), relatively positive δ13C-DIC values (4‰ average), and no detectable higher chain hydrocarbons, NO3−, or SO42−. Bioassay methane production was greatest at the upper interface of the Flowers-Goodale coal bed near the overlying sandstone. Pyrotag analysis identified Aeribacillus as a dominant in situbacterial community member in the coal near the sandstone and statistical analysis indicated Actinobacteria predominated coal core samples compared to claystone or sandstone cores. These bacteria, which previously have been correlated with hydrocarbon-containing environments such as oil reservoirs, have demonstrated the ability to produce biosurfactants to break down hydrocarbons. Identifying microorganisms involved in coal degradation and the hydrogeochemical conditions that promote their activity is crucial to understanding and improving in situ CBM production.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2016.05.001","usgsCitation":"Barnhart, E.P., Weeks, E.P., Jones, E., Ritter, D.J., McIntosh, J.C., Clark, A.C., Ruppert, L.F., Cunningham, A.B., Vinson, D.S., Orem, W.H., and Fields, M.W., 2016, Hydrogeochemistry and coal-associated bacterial populations from a methanogenic coal bed: International Journal of Coal Geology, v. 162, p. 14-26, https://doi.org/10.1016/j.coal.2016.05.001.","productDescription":"13 p.","startPage":"14","endPage":"26","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071554","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":470997,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coal.2016.05.001","text":"Publisher Index Page"},{"id":324277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, Wyoming","otherGeospatial":"Powder River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.97314453125,\n 42.79540065303723\n ],\n [\n -109.97314453125,\n 46.13417004624326\n ],\n [\n -106.06201171875,\n 46.13417004624326\n ],\n [\n -106.06201171875,\n 42.79540065303723\n ],\n [\n -109.97314453125,\n 42.79540065303723\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"162","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576bb6b5e4b07657d1a228b6","chorus":{"doi":"10.1016/j.coal.2016.05.001","url":"http://dx.doi.org/10.1016/j.coal.2016.05.001","publisher":"Elsevier BV","authors":"Barnhart Elliott P., Weeks Edwin P., Jones Elizabeth J.P., Ritter Daniel J., McIntosh Jennifer C., Clark Arthur C., Ruppert Leslie F., Cunningham Alfred B., Vinson David S., Orem William, Fields 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Elizabeth","contributorId":102998,"corporation":false,"usgs":true,"family":"Jones","given":"Elizabeth","email":"","affiliations":[],"preferred":false,"id":640507,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ritter, Daniel J.","contributorId":139869,"corporation":false,"usgs":false,"family":"Ritter","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":13301,"text":"Department of Hydrology and Water Resources, University of Arizona, Tucson, Arizona","active":true,"usgs":false}],"preferred":false,"id":640508,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McIntosh, Jennifer C. 0000-0001-5055-4202","orcid":"https://orcid.org/0000-0001-5055-4202","contributorId":150557,"corporation":false,"usgs":false,"family":"McIntosh","given":"Jennifer","email":"","middleInitial":"C.","affiliations":[{"id":6624,"text":"University of Arizona, Laboratory of Tree-Ring Research","active":true,"usgs":false}],"preferred":false,"id":640509,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Clark, Arthur C. aclark@usgs.gov","contributorId":2320,"corporation":false,"usgs":true,"family":"Clark","given":"Arthur","email":"aclark@usgs.gov","middleInitial":"C.","affiliations":[],"preferred":true,"id":640510,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ruppert, Leslie F. 0000-0002-7453-1061 lruppert@usgs.gov","orcid":"https://orcid.org/0000-0002-7453-1061","contributorId":660,"corporation":false,"usgs":true,"family":"Ruppert","given":"Leslie","email":"lruppert@usgs.gov","middleInitial":"F.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":640511,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cunningham, Alfred B.","contributorId":172389,"corporation":false,"usgs":false,"family":"Cunningham","given":"Alfred","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":640512,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Vinson, David S.","contributorId":172390,"corporation":false,"usgs":false,"family":"Vinson","given":"David","email":"","middleInitial":"S.","affiliations":[{"id":25392,"text":"Department of Geography and Earth Science, University of North Carolina at Charlotte, North Carolina, USA","active":true,"usgs":false}],"preferred":false,"id":640513,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Orem, William H. 0000-0003-4990-0539 borem@usgs.gov","orcid":"https://orcid.org/0000-0003-4990-0539","contributorId":577,"corporation":false,"usgs":true,"family":"Orem","given":"William","email":"borem@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":640514,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Fields, Matthew W.","contributorId":172391,"corporation":false,"usgs":false,"family":"Fields","given":"Matthew","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":640515,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70173799,"text":"70173799 - 2016 - Quantifying resilience","interactions":[],"lastModifiedDate":"2016-06-22T16:04:36","indexId":"70173799","displayToPublicDate":"2016-05-14T02:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying resilience","docAbstract":"The biosphere is under unprecedented pressure, reflected in rapid changes in our global ecological, social, technological and economic systems. In many cases, ecological and social systems can adapt to these changes over time, but when a critical threshold is surpassed, a system under stress can undergo catastrophic change and reorganize into a different state. The concept of resilience, introduced more than 40 years ago in the ecological sciences, captures the behaviour of systems that can occur in alternative states. The original definition of resilience forwarded by Holling (1973) is still the most useful. It defines resilience as the amount of disturbance that a system can withstand before it shifts into an alternative stable state. The idea of alternative stable states has clear and profound implications for ecological management. Coral reefs, for example, are high-diversity systems that provide key ecosystem services such as fisheries and coastal protection. Human impacts are causing significant, ongoing reef degradation, and many reefs have shifted from coral- to algal-dominated states in response to anthropogenic pressures such as elevated water temperatures and overfishing. Understanding and differentiating between the factors that help maintain reefs in coral-dominated states vs. those that facilitate a shift to an undesired algal-dominated state is a critical step towards sound management and conservation of these, and other, important social–ecological systems.
\nResilience has gained popularity among both academicians and laypeople, as a term meant to describe a systems’ ability to withstand disturbance. Resilience has become a buzzword in the last decade, as shown by its increasing appearance in calls for research proposals and scientific citation data bases. The term resilience has in many cases lost the clarity of the original definition and in fact is frequently used in a manner in direct opposition to the original definition. Many current uses of the concept are loose and incorrect. The term is becoming increasingly used in a normative sense (Brand & Jax 2007), as if resilience were a desirable quality of systems. However, even systems in highly undesirable states, such as macro-algae dominated reefs, or city cores in poverty traps, may be highly resilient, which is to say they withstand attempts to transform them into different (desirable) states.
\nOperationalizing the concept of resilience for application and management has been difficult. Misuse of the term can have significant negative impacts, because resilience is being used to help guide responses to natural disasters and to assess the sustainability of ecosystems and urban systems and has been driving international research priorities. Resilience has been argued to be a basic emergent property of systems, a process or a rate. We focus on the original concept as described by Holling, which is that of an emergent system property; when a system is in a desirable state and managers wish to enhance resilience, or when the system is in an undesirable state and managers wish to erode resilience and foster a transformation to an alternative state. Fostering or eroding resilience is a process. When a system is perturbed but resilience is not exceeded, then the recovery can be measured as a rate.
\nSeveral frameworks to operationalize resilience have been proposed. A decade ago, a special feature focused on quantifying resilience was published in the journal Ecosystems (Carpenter, Westley & Turner 2005). The approach there was towards identifying surrogates of resilience, but few of the papers proposed quantifiable metrics. Consequently, many ecological resilience frameworks remain vague and difficult to quantify, a problem that this special feature aims to address. However, considerable progress has been made during the last decade (e.g. Pope, Allen & Angeler 2014). Although some argue that resilience is best kept as an unquantifiable, vague concept (Quinlan et al. 2016), to be useful for managers, there must be concrete guidance regarding how and what to manage and how to measure success (Garmestani, Allen & Benson 2013; Spears et al. 2015). Ideas such as ‘resilience thinking’ have utility in helping stakeholders conceptualize their systems, but provide little guidance on how to make resilience useful for ecosystem management, other than suggesting an ambiguous, Goldilocks approach of being just right (e.g. diverse, but not too diverse; connected, but not too connected). Here, we clarify some prominent resilience terms and concepts, introduce and synthesize the papers in this special feature on quantifying resilience and identify core unanswered questions related to resilience.
","language":"English","publisher":"British Ecological Society","publisherLocation":"London, United Kingdom","doi":"10.1111/1365-2664.12649","usgsCitation":"Allen, C.R., and Angeler, D., 2016, Quantifying resilience: Journal of Applied Ecology, v. 53, p. 617-624, https://doi.org/10.1111/1365-2664.12649.","productDescription":"8 p.","startPage":"617","endPage":"624","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071794","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470999,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.12649","text":"Publisher Index Page"},{"id":324270,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-13","publicationStatus":"PW","scienceBaseUri":"576bb6bae4b07657d1a22941","contributors":{"authors":[{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":638379,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angeler, David G.","contributorId":25027,"corporation":false,"usgs":true,"family":"Angeler","given":"David G.","affiliations":[],"preferred":false,"id":640495,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70176281,"text":"70176281 - 2016 - Decadal-scale export of nitrogen, phosphorus, and sediment from the Susquehanna River basin, USA: Analysis and synthesis of temporal and spatial patterns","interactions":[],"lastModifiedDate":"2016-09-07T12:00:19","indexId":"70176281","displayToPublicDate":"2016-05-14T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Decadal-scale export of nitrogen, phosphorus, and sediment from the Susquehanna River basin, USA: Analysis and synthesis of temporal and spatial patterns","docAbstract":"The export of nitrogen (N), phosphorus (P), and suspended sediment (SS) is a long-standing management concern for the Chesapeake Bay watershed, USA. Here we present a comprehensive evaluation of nutrient and sediment loads over the last three decades at multiple locations in the Susquehanna River basin (SRB), Chesapeake's largest tributary watershed. Sediment and nutrient riverine loadings, including both dissolved and particulate fractions, have generally declined at all sites upstream of Conowingo Dam (non-tidal SRB outlet). Period-of-record declines in riverine yield are generally smaller than those in source input, suggesting the possibility of legacy contributions. Consistent with other watershed studies, these results reinforce the importance of considering lag time between the implementation of management actions and achievement of river quality improvement. Whereas flow-normalized loadings for particulate species have increased recently below Conowingo Reservoir, those for upstream sites have declined, thus substantiating conclusions from prior studies about decreased reservoir trapping efficiency. In regard to streamflow effects, statistically significant log-linear relationships between annual streamflow and annual constituent load suggest the dominance of hydrological control on the inter-annual variability of constituent export. Concentration-discharge relationships revealed general chemostasis and mobilization effects for dissolved and particulate species, respectively, both suggesting transport-limitation conditions. In addition to affecting annual export rates, streamflow has also modulated the relative importance of dissolved and particulate fractions, as reflected by its negative correlations with dissolved P/total P, dissolved N/total N, particulate P/SS, and total N/total P ratios. For land-use effects, period-of-record median annual yields of N, P, and SS all correlate positively with the area fraction of non-forested land but negatively with that of forested land under all hydrological conditions. Overall, this work has informed understanding with respect to four major factors affecting constituent export (i.e., source input, reservoir modulation, streamflow, and land use) and demonstrated the value of long-term river monitoring.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.03.104","usgsCitation":"Zhang, Q., Ball, W.P., and Moyer, D.L., 2016, Decadal-scale export of nitrogen, phosphorus, and sediment from the Susquehanna River basin, USA: Analysis and synthesis of temporal and spatial patterns: Science of the Total Environment, v. 563-564, p. 1016-1029, https://doi.org/10.1016/j.scitotenv.2016.03.104.","productDescription":"14 p.","startPage":"1016","endPage":"1029","ipdsId":"IP-070367","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":471000,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.03.104","text":"Publisher Index Page"},{"id":328310,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, New York, Pennsylvania","otherGeospatial":"Chesapeake Bay, Susquehanna River","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 39.30029918615029\n ],\n [\n -77.51953125,\n 42.309815415686664\n ],\n [\n -75.73974609375,\n 42.309815415686664\n ],\n [\n -75.73974609375,\n 39.30029918615029\n ],\n [\n -77.51953125,\n 39.30029918615029\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"563-564","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57d13a39e4b0571647cf8dbb","contributors":{"authors":[{"text":"Zhang, Qian 0000-0003-0500-5655","orcid":"https://orcid.org/0000-0003-0500-5655","contributorId":174393,"corporation":false,"usgs":false,"family":"Zhang","given":"Qian","email":"","affiliations":[{"id":38802,"text":"University of Maryland Center for Environmental Studies","active":true,"usgs":false}],"preferred":false,"id":648192,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ball, William P.","contributorId":174394,"corporation":false,"usgs":false,"family":"Ball","given":"William","email":"","middleInitial":"P.","affiliations":[{"id":27446,"text":"Johns Hopkins University, Department of Geography and Environmental Engineering","active":true,"usgs":false}],"preferred":false,"id":648193,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moyer, Douglas L. 0000-0001-6330-478X dlmoyer@usgs.gov","orcid":"https://orcid.org/0000-0001-6330-478X","contributorId":174389,"corporation":false,"usgs":true,"family":"Moyer","given":"Douglas","email":"dlmoyer@usgs.gov","middleInitial":"L.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":648191,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70170966,"text":"70170966 - 2016 - Modeled effects of soil acidification on long-term ecological and economic outcomes for managed forests in the Adirondack region (USA)","interactions":[],"lastModifiedDate":"2016-05-13T13:39:46","indexId":"70170966","displayToPublicDate":"2016-05-13T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Modeled effects of soil acidification on long-term ecological and economic outcomes for managed forests in the Adirondack region (USA)","docAbstract":"Sugar maple (Acer saccharum) is among the most ecologically and economically important tree species in North America, and its growth and regeneration is often the focus of silvicultural practices in northern hardwood forests. A key stressor for sugar maple (SM) is acid rain, which depletes base cations from poorly-buffered forest soils and has been associated with much lower SM vigor, growth, and recruitment. However, the potential interactions between forest management and soil acidification – and their implications for the sustainability of SM and its economic and cultural benefits – have not been investigated. In this study, we simulated the development of 50 extant SM stands in the western Adirondack region of NY (USA) for 100 years under different soil chemical conditions and silvicultural prescriptions. We found that interactions between management prescription and soil base saturation will strongly shape the ability to maintain SM in managed forests. Below 12% base saturation, SM did not regenerate sufficiently after harvest and was replaced mainly by red maple (Acer rubrum) and American beech (Fagus grandifolia). Loss of SM on acid-impaired sites was predicted regardless of whether the shelterwood or diameter-limit prescriptions were used. On soils with sufficient base saturation, models predicted that SM will regenerate after harvest and be sustained for future rotations. We then estimated how these different post-harvest outcomes, mediated by acid impairment of forest soils, would affect the potential monetary value of ecosystem services provided by SM forests. Model simulations indicated that a management strategy focused on syrup production – although not feasible across the vast areas where acid impairment has occurred – may generate the greatest economic return. Although pollution from acid rain is declining, its long-term legacy in forest soils will shape future options for sustainable forestry and ecosystem stewardship in the northern hardwood forests of North America.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.scitotenv.2016.04.008","collaboration":"New York State Energy Research and Development Authority; USGS","usgsCitation":"Caputo, J., Beier, C.M., Sullivan, T.J., and Lawrence, G.B., 2016, Modeled effects of soil acidification on long-term ecological and economic outcomes for managed forests in the Adirondack region (USA): Science of the Total Environment, v. 565, p. 401-411, https://doi.org/10.1016/j.scitotenv.2016.04.008.","productDescription":"11 p.","startPage":"401","endPage":"411","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073095","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":471002,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.04.008","text":"Publisher Index 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glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629267,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170245,"text":"ds992 - 2016 - Long-term trends in naturalized rainbow trout (Oncorhynchus mykiss) populations in the upper Esopus Creek, Ulster County, New York, 2009–15","interactions":[],"lastModifiedDate":"2016-05-13T10:52:04","indexId":"ds992","displayToPublicDate":"2016-05-13T09:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"992","title":"Long-term trends in naturalized rainbow trout (Oncorhynchus mykiss) populations in the upper Esopus Creek, Ulster County, New York, 2009–15","docAbstract":"The U.S. Geological Survey, in cooperation with Cornell Cooperative Extension of Ulster County, New York State Energy Research and Development Authority, the New York State Department of Environmental Conservation, and the New York City Department of Environmental Protection, surveyed fish communities annually on the main stem and tributaries of the upper Esopus Creek, Ulster County, New York, from 2009 to 2015. This report summarizes the density, biomass, and size structure of rainbow trout (Oncorhynchus mykiss) and brown trout (Salmo trutta) populations from the 2015 surveys along with data from the preceding 6 years. The mean density of rainbow trout populations in 2015 was 98 fish per 0.1 hectare, which was the highest value observed since 2010, and the mean biomass of rainbow trout populations in 2015 was 864 grams per 0.1 hectare, which was the highest value observed since 2012.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds992","collaboration":"Prepared in cooperation with Cornell Cooperative Extension of Ulster County, New York State Energy Research and Development Authority, the New York State Department of Environmental Conservation, and the New York City Department of Environmental Protection","usgsCitation":"George, S.D., and Baldigo, B.P., 2016, Long-term trends in naturalized rainbow trout (Oncorhynchus mykiss) populations in the upper Esopus Creek, Ulster County, New York, 2009–15: U.S. Geological Survey Data Series 992, 12 p., https://dx.doi.org/10.3133/ds992.","productDescription":"iv, 12 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070172","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":321177,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0992/coverthb.jpg"},{"id":321178,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0992/ds992.pdf","text":"Report","size":"6.49 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 992"}],"country":"United States","state":"New York","county":"Ulster County","otherGeospatial":"Upper Esopus Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.566667,\n 42.216667\n ],\n [\n -74.566667,\n 41.916667\n ],\n [\n -74.066667,\n 41.916667\n ],\n [\n -74.066667,\n 42.216667\n ],\n [\n -74.566667,\n 42.216667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180-8349
Information requests:
(518) 285-5602
Or visit our Web site at:
http://ny.water.usgs.gov
The software program, QRev computes the discharge from moving-boat acoustic Doppler current profiler measurements using data collected with any of the Teledyne RD Instrument or SonTek bottom tracking acoustic Doppler current profilers. The computation of discharge is independent of the manufacturer of the acoustic Doppler current profiler because QRev applies consistent algorithms independent of the data source. In addition, QRev automates filtering and quality checking of the collected data and provides feedback to the user of potential quality issues with the measurement. Various statistics and characteristics of the measurement, in addition to a simple uncertainty assessment are provided to the user to assist them in properly rating the measurement. QRev saves an extensible markup language file that can be imported into databases or electronic field notes software. The user interacts with QRev through a tablet-friendly graphical user interface. This report is the manual for version 2.8 of QRev.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161052","usgsCitation":"Mueller, D.S., 2016, QRev—Software for computation and quality assurance of acoustic Doppler current profiler moving-boat streamflow measurements—User’s manual for version 2.8: U.S. Geological Survey Open-File Report 2016–1052, 50 p., https://dx.doi.org/10.3133/ofr20161052. ","productDescription":"vii, 50 p.","numberOfPages":"59","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-073112","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":321055,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1052/ofr20161052.pdf","text":"Report","size":"3.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1052"},{"id":321054,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1052/coverthb.jpg"},{"id":324156,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/ofr20161068","text":"Open-File Report 2016–1068 - ","description":"OFR 2016-1052","linkHelpText":"QRev—Software for Computation and Quality Assurance of Acoustic Doppler Current Profiler Moving-Boat Streamflow Measurements—Technical Manual for Version 2.8 "}],"contact":"Chief, USGS Office of Surface Water
415 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
(703) 648-5301
Or visit the Office of Surface Water Web site at: http://water.usgs.gov/osw/
","tableOfContents":"High-elevation aquatic ecosystems are highly vulnerable to climate change, yet relatively few records are available to characterize shifts in ecosystem structure or their underlying mechanisms. Using a long-term dataset on seven alpine lakes (3126 to 3620 m) in Colorado, USA, we show that ice-off dates have shifted seven days earlier over the past 33 years and that spring weather conditions – especially snowfall – drive yearly variation in ice-off timing. In the most well-studied lake, earlier ice-off associated with increases in water residence times, thermal stratification, ion concentrations, dissolved nitrogen, pH, and chlorophyll-a. Mechanistically, low spring snowfall and warm temperatures reduce summer stream flow (increasing lake residence times) but enhance melting of glacial and permafrost ice (increasing lake solute inputs). The observed links among hydrological, chemical, and biological responses to climate factors highlight the potential for major shifts in the functioning of alpine lakes due to forecasted climate change.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2016GL069036","usgsCitation":"Preston, D.L., Caine, N., McKnight, D.M., Williams, M.W., Hell, K., Miller, M.P., Hart, S.J., and Johnson, P.T., 2016, Climate regulates alpine lake ice cover phenology and aquatic ecosystem structure: Geophysical Research Letters, v. 43, no. 10, p. 5353-5360, https://doi.org/10.1002/2016GL069036.","productDescription":"8 p.","startPage":"5353","endPage":"5360","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065721","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":471008,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doaj.org/article/74a41412b86246d8b0d27b74c0bce459","text":"Publisher Index Page"},{"id":321123,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","volume":"43","issue":"10","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-28","publicationStatus":"PW","scienceBaseUri":"5734499be4b0dae0d5dd68f4","contributors":{"authors":[{"text":"Preston, Daniel L.","contributorId":58581,"corporation":false,"usgs":true,"family":"Preston","given":"Daniel","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":629149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caine, Nel","contributorId":169277,"corporation":false,"usgs":false,"family":"Caine","given":"Nel","email":"","affiliations":[],"preferred":false,"id":629150,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":629151,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Mark W.","contributorId":43046,"corporation":false,"usgs":true,"family":"Williams","given":"Mark","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":629152,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hell, Katherina","contributorId":169278,"corporation":false,"usgs":false,"family":"Hell","given":"Katherina","email":"","affiliations":[],"preferred":false,"id":629153,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, Matthew P. 0000-0002-2537-1823 mamiller@usgs.gov","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":3919,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew","email":"mamiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":628924,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hart, Sarah J.","contributorId":169279,"corporation":false,"usgs":false,"family":"Hart","given":"Sarah","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":629154,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Johnson, Pieter T.J.","contributorId":28508,"corporation":false,"usgs":true,"family":"Johnson","given":"Pieter","email":"","middleInitial":"T.J.","affiliations":[],"preferred":false,"id":629155,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70170887,"text":"70170887 - 2016 - The importance of base flow in sustaining surface water flow in the Upper Colorado River Basin","interactions":[],"lastModifiedDate":"2016-06-24T11:29:05","indexId":"70170887","displayToPublicDate":"2016-05-11T12:15:00","publicationYear":"2016","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":"The importance of base flow in sustaining surface water flow in the Upper Colorado River Basin","docAbstract":"The Colorado River has been identified as the most overallocated river in the world. Considering predicted future imbalances between water supply and demand and the growing recognition that base flow (a proxy for groundwater discharge to streams) is critical for sustaining flow in streams and rivers, there is a need to develop methods to better quantify present-day base flow across large regions. We adapted and applied the spatially referenced regression on watershed attributes (SPARROW) water quality model to assess the spatial distribution of base flow, the fraction of streamflow supported by base flow, and estimates of and potential processes contributing to the amount of base flow that is lost during in-stream transport in the Upper Colorado River Basin (UCRB). On average, 56% of the streamflow in the UCRB originated as base flow, and precipitation was identified as the dominant driver of spatial variability in base flow at the scale of the UCRB, with the majority of base flow discharge to streams occurring in upper elevation watersheds. The model estimates an average of 1.8 × 1010 m3/yr of base flow in the UCRB; greater than 80% of which is lost during in-stream transport to the Lower Colorado River Basin via processes including evapotranspiration and water diversion for irrigation. Our results indicate that surface waters in the Colorado River Basin are dependent on base flow, and that management approaches that consider groundwater and surface water as a joint resource will be needed to effectively manage current and future water resources in the Basin.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2015WR017963","usgsCitation":"Miller, M.P., Buto, S.G., Susong, D.D., and Rumsey, C., 2016, The importance of base flow in sustaining surface water flow in the Upper Colorado River Basin: Water Resources Research, v. 52, no. 5, p. 3547-3562, https://doi.org/10.1002/2015WR017963.","productDescription":"16 p.","startPage":"3547","endPage":"3562","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068216","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":471007,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015wr017963","text":"Publisher Index Page"},{"id":321122,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","otherGeospatial":"Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.357421875,\n 35.88905007936091\n ],\n [\n -111.357421875,\n 43.389081939117496\n ],\n [\n -105.8203125,\n 43.389081939117496\n ],\n [\n -105.8203125,\n 35.88905007936091\n ],\n [\n -111.357421875,\n 35.88905007936091\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"52","issue":"5","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-09","publicationStatus":"PW","scienceBaseUri":"5734499ee4b0dae0d5dd6915","contributors":{"authors":[{"text":"Miller, Matthew P. 0000-0002-2537-1823 mamiller@usgs.gov","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":3919,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew","email":"mamiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":628925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buto, Susan G. 0000-0002-1107-9549 sbuto@usgs.gov","orcid":"https://orcid.org/0000-0002-1107-9549","contributorId":1057,"corporation":false,"usgs":true,"family":"Buto","given":"Susan","email":"sbuto@usgs.gov","middleInitial":"G.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629146,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Susong, David D. ddsusong@usgs.gov","contributorId":1040,"corporation":false,"usgs":true,"family":"Susong","given":"David","email":"ddsusong@usgs.gov","middleInitial":"D.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629147,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rumsey, Christine 0000-0001-7536-750X crumsey@usgs.gov","orcid":"https://orcid.org/0000-0001-7536-750X","contributorId":146240,"corporation":false,"usgs":true,"family":"Rumsey","given":"Christine","email":"crumsey@usgs.gov","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629148,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170896,"text":"70170896 - 2016 - Ephemerality of discrete methane vents in lake sediments","interactions":[],"lastModifiedDate":"2016-06-02T11:16:13","indexId":"70170896","displayToPublicDate":"2016-05-11T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Ephemerality of discrete methane vents in lake sediments","docAbstract":"Methane is a potent greenhouse gas whose emission from sediments in inland waters and shallow oceans may both contribute to global warming and be exacerbated by it. The fraction of methane emitted by sediments that bypasses dissolution in the water column and reaches the atmosphere as bubbles depends on the mode and spatiotemporal characteristics of venting from the sediments. Earlier studies have concluded that hot spots—persistent, high-flux vents—dominate the regional ebullitive flux from submerged sediments. Here the spatial structure, persistence, and variability in the intensity of methane venting are analyzed using a high-resolution multibeam sonar record acquired at the bottom of a lake during multiple deployments over a 9 month period. We confirm that ebullition is strongly episodic, with distinct regimes of high flux and low flux largely controlled by changes in hydrostatic pressure. Our analysis shows that the spatial pattern of ebullition becomes homogeneous at the sonar's resolution over time scales of hours (for high-flux periods) or days (for low-flux periods), demonstrating that vents are ephemeral rather than persistent, and suggesting that long-term, lake-wide ebullition dynamics may be modeled without resolving the fine-scale spatial structure of venting.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2016GL068668","usgsCitation":"Scandella, B.P., Pillsbury, L., Weber, T., Ruppel, C., Hemond, H.F., and Juanes, R., 2016, Ephemerality of discrete methane vents in lake sediments: Geophysical Research Letters, v. 43, no. 9, p. 4374-4381, https://doi.org/10.1002/2016GL068668.","productDescription":"8 p.","startPage":"4374","endPage":"4381","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073937","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471009,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl068668","text":"Publisher Index Page"},{"id":321118,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"9","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-04","publicationStatus":"PW","scienceBaseUri":"5734499ce4b0dae0d5dd68f8","contributors":{"authors":[{"text":"Scandella, Benjamin P.","contributorId":169274,"corporation":false,"usgs":false,"family":"Scandella","given":"Benjamin","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":628958,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pillsbury, Liam","contributorId":169275,"corporation":false,"usgs":false,"family":"Pillsbury","given":"Liam","email":"","affiliations":[],"preferred":false,"id":628959,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weber, Thomas","contributorId":50095,"corporation":false,"usgs":true,"family":"Weber","given":"Thomas","affiliations":[],"preferred":false,"id":628960,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruppel, Carolyn D. 0000-0003-2284-6632 cruppel@usgs.gov","orcid":"https://orcid.org/0000-0003-2284-6632","contributorId":145770,"corporation":false,"usgs":true,"family":"Ruppel","given":"Carolyn D.","email":"cruppel@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":628957,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hemond, Harold F.","contributorId":34673,"corporation":false,"usgs":false,"family":"Hemond","given":"Harold","email":"","middleInitial":"F.","affiliations":[{"id":13299,"text":"Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA","active":true,"usgs":false}],"preferred":false,"id":628961,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Juanes, Ruben","contributorId":169276,"corporation":false,"usgs":false,"family":"Juanes","given":"Ruben","affiliations":[],"preferred":false,"id":628962,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70169226,"text":"ofr20161051 - 2016 - Streamflow, water quality and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2014","interactions":[],"lastModifiedDate":"2016-05-11T10:59:07","indexId":"ofr20161051","displayToPublicDate":"2016-05-11T11:45:00","publicationYear":"2016","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":"2016-1051","title":"Streamflow, water quality and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2014","docAbstract":"Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate loads of sodium and chloride during water year (WY) 2014 (October 1, 2013, through September 30, 2014) for tributaries to the Scituate Reservoir, Rhode Island. Streamflow and water-quality data used in the study were collected by the U.S. Geological Survey and the Providence Water Supply Board in the cooperative study. Streamflow was measured or estimated by the U.S. Geological Survey following standard methods at 23 streamgages; 14 of these streamgages are equipped with instrumentation capable of continuously monitoring water level, specific conductance, and water temperature. Water-quality samples were collected at 37 sampling stations by the Providence Water Supply Board and at 14 continuous-record streamgages by the U.S. Geological Survey during WY 2014 as part of a long-term sampling program; all stations are in the Scituate Reservoir drainage area. Water-quality data collected by the Providence Water Supply Board are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2014.
The largest tributary to the reservoir (the Ponaganset River, which was monitored by the U.S. Geological Survey) contributed a mean streamflow of 23 cubic feet per second to the reservoir during WY 2014. For the same time period, annual mean streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.35 to about 14 cubic feet per second. Together, tributaries (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,200,000 kilograms of sodium and 2,100,000 kilograms of chloride to the Scituate Reservoir during WY 2014; sodium and chloride yields for the tributaries ranged from 7,700 to 45,000 kilograms per year per square mile and from 12,000 to 75,000 kilograms per year per square mile, respectively.
At the stations where water-quality samples were collected by the Providence Water Supply Board, the median of the median chloride concentrations was 24 milligrams per liter, median nitrite concentration was 0.002 milligrams per liter as nitrogen (N), median nitrate concentration was 0.01 milligrams per liter as N, median orthophosphate concentration was 0.07 milligrams per liter as phosphate, and median concentrations of total coliform bacteria and Escherichia coli were 320 and 20 colony forming units per 100 milliliters, respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and Escherichia coli bacteria were 62 kilograms per day (42 kilograms per day per square mile), 19 grams per day (6.1 grams per day per square mile), 79 grams per day (36 grams per day per square mile), 380 grams per day (150 grams per day per square mile), 13,000 million colony forming units per day (8,300 million colony forming units per day per square mile), and 1,000 million colony forming units per day (470 million colony forming units per day per square mile), respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161051","collaboration":"Prepared in cooperation with the Providence Water Supply Board","usgsCitation":"Smith, K.P., 2016, Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2014: U.S. Geological Survey Open-File Report 2016–1051, 31 p., https://dx.doi.org/10.3133/ofr20161051.","productDescription":"Report: v, 31 p.; Appendix 1","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069938","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":320747,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1051/ofr20161051.pdf","text":"Report","size":"11.1 (MB)","linkFileType":{"id":1,"text":"pdf"},"description":"OF 2016-1051"},{"id":320748,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1051/ofr20161051_appendix1.xlsx","text":"Appendix 1","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 1","linkHelpText":"Appendix 1. Water-quality data collected by the Providence Water Supply Board at 37 monitoring stations in the Scituate Reservoir drainage area, Rhode Island, water year 2014. Excel (30 KB)"},{"id":320746,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1051/coverthb.jpg"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Scituate Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.7572021484375,\n 41.738784653087464\n ],\n [\n -71.7572021484375,\n 41.90304362629451\n ],\n [\n -71.55567169189453,\n 41.90304362629451\n ],\n [\n -71.55567169189453,\n 41.738784653087464\n ],\n [\n -71.7572021484375,\n 41.738784653087464\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
or visit our Web site at:
http://newengland.water.usgs.gov
Compound meander bends with multiple lobes of maximum curvature are common in actively evolving lowland rivers. Interaction among spatial patterns of mean flow, turbulence, bed morphology, bank failures and channel migration in compound bends is poorly understood. In this paper, acoustic Doppler current profiler (ADCP) measurements of the three-dimensional (3D) flow velocities in a compound bend are examined to evaluate the influence of channel curvature and hydrologic variability on the structure of flow within the bend. Flow structure at various flow stages is related to changes in bed morphology over the study timeframe. Increases in local curvature within the upstream lobe of the bend reduce outer bank velocities at morphologically significant flows, creating a region that protects the bank from high momentum flow and high bed shear stresses. The dimensionless radius of curvature in the upstream lobe is one-third less than that of the downstream lobe, with average bank erosion rates less than half of the erosion rates for the downstream lobe. Higher bank erosion rates within the downstream lobe correspond to the shift in a core of high velocity and bed shear stresses toward the outer bank as flow moves through the two lobes. These erosion patterns provide a mechanism for continued migration of the downstream lobe in the near future. Bed material size distributions within the bend correspond to spatial patterns of bed shear stress magnitudes, indicating that bed material sorting within the bend is governed by bed shear stress. Results suggest that patterns of flow, sediment entrainment, and planform evolution in compound meander bends are more complex than in simple meander bends. Moreover, interactions among local influences on the flow, such as woody debris, local topographic steering, and locally high curvature, tend to cause compound bends to evolve toward increasing planform complexity over time rather than stable configurations.
","language":"English","publisher":"John Wiley & Sons","doi":"10.1002/esp.3895","usgsCitation":"Engel, F.L., and Rhoads, B.L., 2016, Three-dimensional flow structure and patterns of bed shear stress in an evolving compound meander bend: Earth Surface Processes and Landforms, v. 41, no. 9, p. 1211-1226, https://doi.org/10.1002/esp.3895.","productDescription":"16 p.","startPage":"1211","endPage":"1226","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059802","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":321116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"9","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-15","publicationStatus":"PW","scienceBaseUri":"5734499ee4b0dae0d5dd691b","contributors":{"authors":[{"text":"Engel, Frank L. 0000-0002-4253-2625 fengel@usgs.gov","orcid":"https://orcid.org/0000-0002-4253-2625","contributorId":5463,"corporation":false,"usgs":true,"family":"Engel","given":"Frank","email":"fengel@usgs.gov","middleInitial":"L.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629142,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rhoads, Bruce L.","contributorId":20248,"corporation":false,"usgs":true,"family":"Rhoads","given":"Bruce","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":629143,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70170899,"text":"70170899 - 2016 - Regional-scale controls on dissolved nitrous oxide in the Upper Mississippi River","interactions":[],"lastModifiedDate":"2016-06-02T11:14:56","indexId":"70170899","displayToPublicDate":"2016-05-11T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Regional-scale controls on dissolved nitrous oxide in the Upper Mississippi River","docAbstract":"The U.S. Corn Belt is one of the most intensive agricultural regions of the world and is drained by the Upper Mississippi River (UMR), which forms one of the largest drainage basins in the U.S. While the effects of agricultural nitrate (NO3-) on water quality in the UMR have been well documented, its impact on the production of nitrous oxide (N2O) has not been reported. Using a novel equilibration technique, we present the largest data set of freshwater dissolved N2O concentrations (0.7 to 6 times saturation) and examine the controls on its variability over a 350 km reach of the UMR. Driven by a supersaturated water column, the UMR was an important atmospheric N2O source (+68 mg N2ONm-2 yr-1) that varies nonlinearly with the NO3-concentration. Our analyses indicated that a projected doubling of the NO3-concentration by 2050 would cause dissolved N2O concentrations and emissions to increase by about 40%.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2016GL068710","usgsCitation":"Turner, P., Griffis, T., Baker, J., Lee, X., Crawford, J.T., Loken, L., and Venterea, R., 2016, Regional-scale controls on dissolved nitrous oxide in the Upper Mississippi River: Geophysical Research Letters, v. 43, no. 9, p. 4400-4407, https://doi.org/10.1002/2016GL068710.","productDescription":"8 p.","startPage":"4400","endPage":"4407","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071258","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":471012,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl068710","text":"Publisher Index Page"},{"id":321112,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Mississippi River","volume":"43","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-06","publicationStatus":"PW","scienceBaseUri":"5734499ce4b0dae0d5dd6903","contributors":{"authors":[{"text":"Turner, P.A.","contributorId":169214,"corporation":false,"usgs":false,"family":"Turner","given":"P.A.","email":"","affiliations":[{"id":25441,"text":"University of Minnesota, Department of Soil, Water and Climate","active":true,"usgs":false}],"preferred":false,"id":628997,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Griffis, T.J.","contributorId":169215,"corporation":false,"usgs":false,"family":"Griffis","given":"T.J.","email":"","affiliations":[{"id":25442,"text":"U.S. Department of Agriculture - Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":628998,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baker, J.M.","contributorId":169216,"corporation":false,"usgs":false,"family":"Baker","given":"J.M.","email":"","affiliations":[{"id":25443,"text":"Yale University, School of Forestry and Environmental Studies","active":true,"usgs":false}],"preferred":false,"id":628999,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lee, X.","contributorId":169217,"corporation":false,"usgs":false,"family":"Lee","given":"X.","email":"","affiliations":[{"id":25444,"text":"Yale-Nanjing University of Information, Science and Technology","active":true,"usgs":false}],"preferred":false,"id":629000,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Crawford, John T. 0000-0003-4440-6945 jtcrawford@usgs.gov","orcid":"https://orcid.org/0000-0003-4440-6945","contributorId":4081,"corporation":false,"usgs":true,"family":"Crawford","given":"John","email":"jtcrawford@usgs.gov","middleInitial":"T.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":628996,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Loken, Luke C. lloken@usgs.gov","contributorId":169218,"corporation":false,"usgs":true,"family":"Loken","given":"Luke C.","email":"lloken@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":629001,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Venterea, R.T.","contributorId":53994,"corporation":false,"usgs":true,"family":"Venterea","given":"R.T.","email":"","affiliations":[],"preferred":false,"id":629002,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70170902,"text":"70170902 - 2016 - The ecology of methane in streams and rivers: Patterns, controls, and global significance","interactions":[],"lastModifiedDate":"2016-05-11T10:34:05","indexId":"70170902","displayToPublicDate":"2016-05-11T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1459,"text":"Ecological Monographs","active":true,"publicationSubtype":{"id":10}},"title":"The ecology of methane in streams and rivers: Patterns, controls, and global significance","docAbstract":"Streams and rivers can substantially modify organic carbon (OC) inputs from terrestrial landscapes, and much of this processing is the result of microbial respiration. While carbon dioxide (CO2) is the major end-product of ecosystem respiration, methane (CH4) is also present in many fluvial environments even though methanogenesis typically requires anoxic conditions that may be scarce in these systems. Given recent recognition of the pervasiveness of this greenhouse gas in streams and rivers, we synthesized existing research and data to identify patterns and drivers of CH4, knowledge gaps, and research opportunities. This included examining the history of lotic CH4 research, creating a database of concentrations and fluxes (MethDB) to generate a global-scale estimate of fluvial CH4 efflux, and developing a conceptual framework and using this framework to consider how human activities may modify fluvial CH4 dynamics. Current understanding of CH4 in streams and rivers has been strongly influenced by goals of understanding OC processing and quantifying the contribution of CH4 to ecosystem C fluxes. Less effort has been directed towards investigating processes that dictate in situ CH4 production and loss. CH4 makes a meager contribution to watershed or landscape C budgets, but streams and rivers are often significant CH4 sources to the atmosphere across these same spatial extents. Most fluvial systems are supersaturated with CH4 and we estimate an annual global emission of 26.8 Tg CH4, equivalent to ~15-40% of wetland and lake effluxes, respectively. Less clear is the role of CH4 oxidation, methanogenesis, and total anaerobic respiration to whole ecosystem production and respiration. Controls on CH4 generation and persistence can be viewed in terms of proximate controls that influence methanogenesis (organic matter, temperature, alternative electron acceptors, nutrients) and distal geomorphic and hydrologic drivers. Multiple controls combined with its extreme redox status and low solubility result in high spatial and temporal variance of CH4 in fluvial environments, which presents a substantial challenge for understanding its larger-scale dynamics. Further understanding of CH4 production and consumption, anaerobic metabolism, and ecosystem energetics in streams and rivers can be achieved through more directed studies and comparison with knowledge from terrestrial, wetland, and aquatic disciplines.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/15-1027.1","usgsCitation":"Stanley, E.H., Casson, N.J., Christel, S.T., Crawford, J.T., Loken, L., and Oliver, S., 2016, The ecology of methane in streams and rivers: Patterns, controls, and global significance: Ecological Monographs, v. 86, no. 2, p. 146-171, https://doi.org/10.1890/15-1027.1.","productDescription":"16 p.","startPage":"146","endPage":"171","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066395","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":471013,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10680/1574","text":"External Repository"},{"id":321111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"86","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-07","publicationStatus":"PW","scienceBaseUri":"5734499de4b0dae0d5dd690d","contributors":{"authors":[{"text":"Stanley, Emily H.","contributorId":55725,"corporation":false,"usgs":false,"family":"Stanley","given":"Emily","email":"","middleInitial":"H.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":629004,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Casson, Nora J.","contributorId":169271,"corporation":false,"usgs":false,"family":"Casson","given":"Nora","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":629005,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Christel, Samuel T.","contributorId":169272,"corporation":false,"usgs":false,"family":"Christel","given":"Samuel","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":629006,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crawford, John T. 0000-0003-4440-6945 jtcrawford@usgs.gov","orcid":"https://orcid.org/0000-0003-4440-6945","contributorId":4081,"corporation":false,"usgs":true,"family":"Crawford","given":"John","email":"jtcrawford@usgs.gov","middleInitial":"T.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":629003,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loken, Luke C. lloken@usgs.gov","contributorId":169218,"corporation":false,"usgs":true,"family":"Loken","given":"Luke C.","email":"lloken@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":629007,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Oliver, Samantha K.","contributorId":169273,"corporation":false,"usgs":false,"family":"Oliver","given":"Samantha K.","affiliations":[],"preferred":false,"id":629008,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70188601,"text":"70188601 - 2016 - A study of the 2015 Mw 8.3 Illapel earthquake and tsunami: Numerical and analytical approaches","interactions":[],"lastModifiedDate":"2017-06-16T12:23:37","indexId":"70188601","displayToPublicDate":"2016-05-11T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3208,"text":"Pure and Applied Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"A study of the 2015 Mw 8.3 Illapel earthquake and tsunami: Numerical and analytical approaches","docAbstract":"The September 16, 2015 Illapel, Chile earthquake\ntriggered a large tsunami, causing both economic losses and\nfatalities. To study the coastal effects of this earthquake, and to\nunderstand how such hazards might be accurately modeled in the\nfuture, different finite fault models of the Illapel rupture are used to\ndefine the initial condition for tsunami simulation. The numerical\ncode Non-hydrostatic Evolution of Ocean WAVEs (NEOWAVE)\nis employed to model the tsunami evolution through the Pacific\nOcean. Because only a short time is available for emergency\nresponse, and since the earthquake and tsunami sources are close to\nthe coast, gaining a rapid understanding of the near-field run-up\nbehavior is highly relevant to Chile. Therefore, an analytical\nsolution of the 2 ? 1 D shallow water wave equations is considered.\nWith this solution, we show that we can quickly estimate the\nrun-up distribution along the coastline, to first order. After the\nearthquake and tsunami, field observations were measured in the\nsurrounded coastal region, where the tsunami resulted in significant\nrun-up. First, we compare the analytical and numerical solutions to\ntest the accuracy of the analytical approach and the field observations,\nimplying the analytic approach can accurately model tsunami\nrun-up after an earthquake, without sacrificing the time necessary\nfor a full numerical inversion. Then, we compare both with field\nrun-up measurements. We observe the consistency between the two\napproaches. To complete the analysis, a tsunami source inversion is\nperformed using run-up field measurements only. These inversion\nresults are compared with seismic models, and are shown to capture\nthe broad-scale details of those models, without the necessity of the\ndetailed data sets they invert.","language":"English","publisher":"SpringerLink","doi":"10.1007/s00024-016-1305-0","usgsCitation":"Fuentes, M., Riquelme, S., Hayes, G.P., Medina, M., Melgar, D., Vargas, G., Gonzalez, J., and Villalobos, A., 2016, A study of the 2015 Mw 8.3 Illapel earthquake and tsunami: Numerical and analytical approaches: Pure and Applied Geophysics, v. 173, p. 1847-1858, https://doi.org/10.1007/s00024-016-1305-0.","productDescription":"12 p. 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2016 - POLARIS: A 30-meter probabilistic soil series map of the contiguous United States","interactions":[],"lastModifiedDate":"2017-08-29T09:50:15","indexId":"70170912","displayToPublicDate":"2016-05-10T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1760,"text":"Geoderma","active":true,"publicationSubtype":{"id":10}},"title":"POLARIS: A 30-meter probabilistic soil series map of the contiguous United States","docAbstract":"A new complete map of soil series probabilities has been produced for the contiguous United States at a 30 m spatial resolution. This innovative database, named POLARIS, is constructed using available high-resolution geospatial environmental data and a state-of-the-art machine learning algorithm (DSMART-HPC) to remap the Soil Survey Geographic (SSURGO) database. This 9 billion grid cell database is possible using available high performance computing resources. POLARIS provides a spatially continuous, internally consistent, quantitative prediction of soil series. It offers potential solutions to the primary weaknesses in SSURGO: 1) unmapped areas are gap-filled using survey data from the surrounding regions, 2) the artificial discontinuities at political boundaries are removed, and 3) the use of high resolution environmental covariate data leads to a spatial disaggregation of the coarse polygons. The geospatial environmental covariates that have the largest role in assembling POLARIS over the contiguous United States (CONUS) are fine-scale (30 m) elevation data and coarse-scale (~ 2 km) estimates of the geographic distribution of uranium, thorium, and potassium. A preliminary validation of POLARIS using the NRCS National Soil Information System (NASIS) database shows variable performance over CONUS. In general, the best performance is obtained at grid cells where DSMART-HPC is most able to reduce the chance of misclassification. The important role of environmental covariates in limiting prediction uncertainty suggests including additional covariates is pivotal to improving POLARIS' accuracy. This database has the potential to improve the modeling of biogeochemical, water, and energy cycles in environmental models; enhance availability of data for precision agriculture; and assist hydrologic monitoring and forecasting to ensure food and water security.
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USA","active":true,"usgs":false}],"preferred":false,"id":629053,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McBratney, Alexander B","contributorId":169245,"corporation":false,"usgs":false,"family":"McBratney","given":"Alexander B","affiliations":[{"id":25455,"text":"Department of Environmental Sciences, Faculty of Agriculture and Environment, The University of Sydney, Sydney, Australia","active":true,"usgs":false}],"preferred":false,"id":629055,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hempel, Jonathan W","contributorId":169244,"corporation":false,"usgs":false,"family":"Hempel","given":"Jonathan","email":"","middleInitial":"W","affiliations":[{"id":25454,"text":"National Soil Survey Center, NRCS, Lincoln, Nebraska, USA","active":true,"usgs":false}],"preferred":false,"id":629054,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nauman, Travis W. 0000-0001-8004-0608 tnauman@usgs.gov","orcid":"https://orcid.org/0000-0001-8004-0608","contributorId":169241,"corporation":false,"usgs":true,"family":"Nauman","given":"Travis","email":"tnauman@usgs.gov","middleInitial":"W.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":629051,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brungard, Colby W.","contributorId":99488,"corporation":false,"usgs":true,"family":"Brungard","given":"Colby","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":629056,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Odgers, Nathan P","contributorId":169246,"corporation":false,"usgs":false,"family":"Odgers","given":"Nathan","email":"","middleInitial":"P","affiliations":[{"id":25454,"text":"National Soil Survey Center, NRCS, Lincoln, Nebraska, USA","active":true,"usgs":false}],"preferred":false,"id":629057,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70171093,"text":"70171093 - 2016 - Mid-latitude shrub steppe plant communities: Climate change consequences for soil water resources","interactions":[],"lastModifiedDate":"2016-09-06T14:03:13","indexId":"70171093","displayToPublicDate":"2016-05-10T09:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Mid-latitude shrub steppe plant communities: Climate change consequences for soil water resources","docAbstract":"In the coming century, climate change is projected to impact precipitation and temperature regimes worldwide, with especially large effects in drylands. We use big sagebrush ecosystems as a model dryland ecosystem to explore the impacts of altered climate on ecohydrology and the implications of those changes for big sagebrush plant communities using output from 10 Global Circulation Models (GCMs) for two representative concentration pathways (RCPs). We ask: 1) What is the magnitude of variability in future temperature and precipitation regimes among GCMs and RCPs for big sagebrush ecosystems and 2) How will altered climate and uncertainty in climate forecasts influence key aspects of big sagebrush water balance? We explored these questions across 1980-2010, 2030-2060, and 2070-2100 to determine how changes in water balance might develop through the 21st century. We assessed ecohydrological variables at 898 sagebrush sites across the western US using a process-based soil water model, SOILWAT to model all components of daily water balance using site-specific vegetation parameters and site-specific soil properties for multiple soil layers. Our modeling approach allowed for changes in vegetation based on climate. Temperature increased across all GCMs and RCPs, while changes in precipitation were more variable across GCMs. Winter and spring precipitation was predicted to increase in the future (7% by 2030-2060, 12% by 2070-2100), resulting in slight increases in soil water potential (SWP) in winter. Despite wetter winter soil conditions, SWP decreased in late spring and summer due to increased evapotranspiration (6% by 2030-2060, 10% by 2070-2100) and groundwater recharge (26% and 30% increase by 2030-2060 and 2070-2100). Thus, despite increased precipitation in the cold season, soils may dry out earlier in the year, resulting in potentially longer drier summer conditions. If winter precipitation cannot offset drier summer conditions in the future, we expect big sagebrush regeneration and survival will be negatively impacted, potentially resulting in shifts in the relative abundance of big sagebrush plant functional groups. Our results also highlight the importance of assessing multiple GCMs to understand the range of climate change outcomes on ecohydrology, which was contingent on the GCM chosen.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.1457","usgsCitation":"Palmquist, K.A., Schlaepfer, D., Bradford, J.B., and Lauenroth, W.K., 2016, Mid-latitude shrub steppe plant communities: Climate change consequences for soil water resources: Ecology, v. 97, no. 9, p. 2342-2354, https://doi.org/10.1002/ecy.1457.","productDescription":"13 p.","startPage":"2342","endPage":"2354","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066807","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":321445,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5740354de4b07e28b65e9697","contributors":{"authors":[{"text":"Palmquist, Kyle A.","contributorId":169517,"corporation":false,"usgs":false,"family":"Palmquist","given":"Kyle","email":"","middleInitial":"A.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":629844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schlaepfer, Daniel R.","contributorId":105189,"corporation":false,"usgs":false,"family":"Schlaepfer","given":"Daniel R.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":629846,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":629843,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lauenroth, Willliam K.","contributorId":169518,"corporation":false,"usgs":false,"family":"Lauenroth","given":"Willliam","email":"","middleInitial":"K.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":629845,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70186267,"text":"70186267 - 2016 - Use of mussel casts from archaeological sites as paleoecological indicators: An example from CA-MRN-254, Marin County, Alta California","interactions":[],"lastModifiedDate":"2017-04-03T12:50:32","indexId":"70186267","displayToPublicDate":"2016-05-09T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5361,"text":"California Archaeology","active":true,"publicationSubtype":{"id":10}},"title":"Use of mussel casts from archaeological sites as paleoecological indicators: An example from CA-MRN-254, Marin County, Alta California","docAbstract":"Archaeological investigations at prehistoric site CA-MRN-254 at the Dominican University of California in Marin County, California, revealed evidence of Native American occupation spanning the past 1,800 years. A dominant source of food for the inhabitants in the San Francisco Bay area was the intertidal, quiet-water dwelling blue mussel (Mytilus trossulus), although rare occurrences of the open coast-dwelling California mussel (Mytilus californianus) suggest that this species was also utilized sporadically. On rare occasions, cultural horizons at this site contain abundant sediment-filled casts of the smaller mussel Modiolus sp. These casts were formed soon after death when the shells filled with sediment and were roasted along with living bivalve shellfish for consumption. Thin sections of these mussel casts display sedimentological and microbiological constituents that shed light on the paleoenvironmental conditions when they were alive. Fine-grained sediment and pelletal muds comprising these casts suggest that the mussels were collected in a low energy, inner bay environment. The rare presence of the diatoms Triceratium dubium and Thalassionema nitzschioides indicate more normal marine (35 psu) and possibly warmer conditions than presently exist in San Francisco Bay. Radiocarbon dating of charcoal associated with the mussel casts containing these diatoms correlates with a 600-year period of warming from ca. A.D. 700–1300, known as the Medieval Climatic Anomaly. Results of this mussel cast study demonstrate that they have great potential for providing paleoenvironmental information at this and other archaeological sites.
","language":"English","publisher":"Society for California Archaeology","publisherLocation":"Chico, CA","doi":"10.1080/1947461X.2016.1176367","usgsCitation":"McGann, M., Starratt, S.W., Powell, C.L., and Bieling, D.G., 2016, Use of mussel casts from archaeological sites as paleoecological indicators: An example from CA-MRN-254, Marin County, Alta California: California Archaeology, v. 8, no. 1, p. 63-90, https://doi.org/10.1080/1947461X.2016.1176367.","productDescription":"28 p.","startPage":"63","endPage":"90","ipdsId":"IP-079316","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":339047,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Rafael","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.51884460449217,\n 37.97786403627176\n ],\n [\n -122.51609802246092,\n 37.97786403627176\n ],\n [\n -122.51609802246092,\n 37.979555414681506\n ],\n [\n -122.51884460449217,\n 37.979555414681506\n ],\n [\n -122.51884460449217,\n 37.97786403627176\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-09","publicationStatus":"PW","scienceBaseUri":"58e35f7fe4b09da67997ecad","contributors":{"authors":[{"text":"McGann, Mary 0000-0002-3057-2945 mmcgann@usgs.gov","orcid":"https://orcid.org/0000-0002-3057-2945","contributorId":169540,"corporation":false,"usgs":true,"family":"McGann","given":"Mary","email":"mmcgann@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":688076,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Starratt, Scott W. 0000-0001-9405-1746 sstarrat@usgs.gov","orcid":"https://orcid.org/0000-0001-9405-1746","contributorId":2891,"corporation":false,"usgs":true,"family":"Starratt","given":"Scott","email":"sstarrat@usgs.gov","middleInitial":"W.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":688077,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powell, Charles L. II 0000-0002-1913-555X cpowell@usgs.gov","orcid":"https://orcid.org/0000-0002-1913-555X","contributorId":3243,"corporation":false,"usgs":true,"family":"Powell","given":"Charles","suffix":"II","email":"cpowell@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":688078,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bieling, David G","contributorId":190292,"corporation":false,"usgs":false,"family":"Bieling","given":"David","email":"","middleInitial":"G","affiliations":[],"preferred":false,"id":688079,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70169357,"text":"sir20165036 - 2016 - Flood-inundation maps for the East Fork White River at Shoals, Indiana","interactions":[],"lastModifiedDate":"2016-05-18T09:55:41","indexId":"sir20165036","displayToPublicDate":"2016-05-06T14:00:00","publicationYear":"2016","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":"2016-5036","title":"Flood-inundation maps for the East Fork White River at Shoals, Indiana","docAbstract":"Digital flood-inundation maps for a 5.9-mile reach of the East Fork White River at Shoals, Indiana (Ind.), were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. 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 East Fork White River at Shoals, Ind. (USGS station number 03373500). Near-real-time stages at this streamgage may be obtained on the Internet from the USGS National Water Information System at http://waterdata.usgs.gov/ or the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS) at http://water.weather.gov/ahps/, which also forecasts flood hydrographs at this site (NWS AHPS site SHLI3). NWS AHPS forecast peak stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation.
Flood profiles were computed for the East Fork White River reach by means of a one-dimensional, step-backwater model developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the current stage-discharge relation (USGS rating no. 43.0) at USGS streamgage 03373500, East Fork White River at Shoals, Ind. The calibrated hydraulic model was then used to compute 26 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from approximately bankfull (10 ft) to the highest stage of the current stage-discharge rating curve (35 ft). The simulated water-surface profiles were then combined with a geographic information system (GIS) digital elevation model (DEM), derived from light detection and ranging (lidar) data, to delineate the area flooded at each water level. The areal extent of the 24-ft flood-inundation map was verified with photographs from a flood event on July 20, 2015.
The availability of these maps, along with information on the Internet regarding current stage from the USGS streamgage at East Fork White River at Shoals, Ind., and forecasted stream stages from the NWS AHPS, provides 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.
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U.S. Geological Survey
5957 Lakeside Blvd
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http://in.water.usgs.gov/
Hydrologic and hydraulic analyses were done for selected reaches of five streams in and near Shelby, Richland County, Ohio. The U.S. Geological Survey (USGS), in cooperation with the Muskingum Watershed Conservancy District, conducted these analyses on the Black Fork Mohican River and four tributaries: Seltzer Park Creek, Seltzer Park Tributary, Tuby Run, and West Branch. Drainage areas of the four stream reaches studied range from 0.51 to 60.3 square miles. The analyses included estimation of the 10-, 2-, 1-, and 0.2-percent annual-exceedance probability (AEP) flood-peak discharges using the USGS Ohio StreamStats application. Peak discharge estimates, along with cross-sectional and hydraulic structure geometries, and estimates of channel roughness coefficients were used as input to step-backwater models. The step-backwater water models were used to determine water-surface elevation profiles of four flood-peak discharges and a regulatory floodway. This study involved the installation of, and data collection at, a streamflow-gaging station (Black Fork Mohican River at Shelby, Ohio, 03129197), precipitation gage (Rain gage at Reservoir Number Two at Shelby, Ohio, 405209082393200), and seven submersible pressure transducers on six selected river reaches. Two precipitation-runoff models, one for the winter events and one for nonwinter events for the headwaters of the Black Fork Mohican River, were developed and calibrated using the data collected. With the exception of the runoff curve numbers, all other parameters used in the two precipitation-runoff models were identical. The Nash-Sutcliffe model efficiency coefficients were 0.737, 0.899, and 0.544 for the nonwinter events and 0.850 and 0.671 for the winter events. Both of the precipitation-runoff models underestimated the total volume of water, with residual runoff ranging from -0.27 inches to -1.53 inches. The results of this study can be used to assess possible mitigation options and define flood hazard areas that will contribute to the protection of life and property. This study could also assist emergency managers, community officials, and residents in determining when flooding may occur and planning evacuation routes during a flood.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155187","collaboration":"Prepared in cooperation with the Muskingum Watershed Conservancy District","usgsCitation":"Huitger, C.A, Ostheimer, C.J., and Koltun, G.F., 2016, Hydrologic and hydraulic analyses for the Black Fork Mohican River Basin in and near Shelby, Ohio: U.S. Geological Survey Scientific Investigations Report 2015–5187, 39 p., 2 appendixes, https://dx.doi.org/10.3133/sir20155187.","productDescription":"Report: vi, 39 p.; 5 Appendixes","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060945","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":320916,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-1.csv","text":"Appendix 1 - Table 1-1","size":"84.1 KB csv","description":"SIR 2015-5187"},{"id":320915,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5187/sir20155187.pdf","text":"Report","size":"1.32 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5187"},{"id":320917,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-2.csv","text":"Appendix 1 - Table 1-2","size":"62 KB csv","description":"SIR 2015-5187"},{"id":320914,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5187/coverthb.jpg"},{"id":320919,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-4.csv","text":"Appendix 1 - Table 1-4","size":"50 KB csv","description":"SIR 2015-5187"},{"id":320918,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-3.csv","text":"Appendix 1 - Table 1-3","size":"19 KB csv","description":"SIR 2015-5187"},{"id":320920,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-5.csv","text":"Appendix 1 - Table 1-5","size":"22 KB csv","description":"SIR 2015-5187"}],"country":"United States","state":"Ohio","city":"Shelby","otherGeospatial":"Black Fork Mohican River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.70902633666992,\n 40.83563216247778\n ],\n [\n -82.70902633666992,\n 40.91934991356069\n ],\n [\n -82.61959075927734,\n 40.91934991356069\n ],\n [\n -82.61959075927734,\n 40.83563216247778\n ],\n [\n -82.70902633666992,\n 40.83563216247778\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio Water Science Center
6480 Doubletree Ave
Columbus, OH 43229
http://oh.water.usgs.gov/