Water quality, habitat, and fish in Minnesota lakes will potentially be facing substantial levels of stress in the coming decades primarily because of two stressors: (1) land-use change (urban and agricultural) and (2) climate change. Several regional and statewide lake modeling studies have identified the potential linkages between land-use and climate change on reductions in the volume of suitable lake habitat for coldwater fish populations. In recent years, water-resource scientists have been making the case for focused assessments and monitoring of sentinel systems to address how these stress agents change lakes over the long term. Currently in Minnesota, a large-scale effort called “Sustaining Lakes in a Changing Environment” is underway that includes a focus on monitoring basic watershed, water quality, habitat, and fish indicators of 24 Minnesota sentinel lakes across a gradient of ecoregions, depths, and nutrient levels. As part of this effort, the U.S. Geological Survey, in cooperation with the Minnesota Department of Natural Resources, developed predictive water quality models to assess water quality and habitat dynamics of three select deepwater lakes in Minnesota. The three lakes (Lake Carlos in Douglas County, Elk Lake in Clearwater County, and Trout Lake in Cook County) were assessed under recent (2010–11) meteorological conditions. The three selected lakes contain deep, coldwater habitats that remain viable during the summer months for coldwater fish species.
\nHydrodynamics and water-quality characteristics for each of the three lakes were simulated using the CE-QUAL-W2 model, which is a carbon-based, laterally averaged, two-dimensional water-quality model. The CE-QUAL-W2 models address the interaction between nutrient cycling, primary production, and trophic dynamics to predict responses in the distribution of temperature and oxygen in lakes.
\nThe CE-QUAL-W2 models for all three lakes successfully predicted water temperature, on the basis of the two metrics of absolute mean error and root mean square error, using measured inputs of water temperature and nutrients. One of the main calibration tools for CE-QUAL-W2 model development was the vertical profile temperature data, available for all three lakes. For all three lakes, the absolute mean error and root mean square error were less than 1.0 degree Celsius and 1.2 degrees Celsius, respectively, for the different depth ranges used for vertical profile comparisons. In Lake Carlos, simulated water temperatures compared better to measured water temperatures in the epilimnion than in the hypolimnion. The reverse was true for the other two lakes, Elk Lake and Trout Lake, where the simulated results were slightly better for the hypolimnion than the epilimnion. The model also was used to approximate the location of the thermocline throughout the simulation periods, approximately April to November, in all three lake models. Deviations between the simulated and measured water temperatures in the vertical lake profile commonly were because of an offset in the timing of thermocline shifts rather than the simulated results missing thermocline shifts altogether.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145066","collaboration":"Prepared in cooperation with the Minnesota Department of Natural Resources","usgsCitation":"Smith, E.A., Kiesling, R.L., Galloway, J.M., and Ziegeweid, J.R., 2014, Water quality and algal community dynamics of three deepwater lakes in Minnesota utilizing CE-QUAL-W2 models: U.S. Geological Survey Scientific Investigations Report 2014-5066, xi, 73 p., https://doi.org/10.3133/sir20145066.","productDescription":"xi, 73 p.","numberOfPages":"90","onlineOnly":"Y","ipdsId":"IP-016416","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":288945,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145066.jpg"},{"id":288939,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5066/"},{"id":288944,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5066/pdf/sir2014-5066.pdf"}],"projection":"Universal Transverse Mercator Zone 15 North","datum":"North American Datum of 1983","country":"United States","state":"Minnesota","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -97.426,43.3158 ], [ -97.426,49.4915 ], [ -89.2941,49.4915 ], [ -89.2941,43.3158 ], [ -97.426,43.3158 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae78a3e4b0abf75cf2dc0e","contributors":{"authors":[{"text":"Smith, Erik A. 0000-0001-8434-0798 easmith@usgs.gov","orcid":"https://orcid.org/0000-0001-8434-0798","contributorId":1405,"corporation":false,"usgs":true,"family":"Smith","given":"Erik","email":"easmith@usgs.gov","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492870,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kiesling, Richard L. 0000-0002-3017-1826 kiesling@usgs.gov","orcid":"https://orcid.org/0000-0002-3017-1826","contributorId":1837,"corporation":false,"usgs":true,"family":"Kiesling","given":"Richard","email":"kiesling@usgs.gov","middleInitial":"L.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492872,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Galloway, Joel M. 0000-0002-9836-9724 jgallowa@usgs.gov","orcid":"https://orcid.org/0000-0002-9836-9724","contributorId":1562,"corporation":false,"usgs":true,"family":"Galloway","given":"Joel","email":"jgallowa@usgs.gov","middleInitial":"M.","affiliations":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492871,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ziegeweid, Jeffrey R. 0000-0001-7797-3044 jrziege@usgs.gov","orcid":"https://orcid.org/0000-0001-7797-3044","contributorId":4166,"corporation":false,"usgs":true,"family":"Ziegeweid","given":"Jeffrey","email":"jrziege@usgs.gov","middleInitial":"R.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492873,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70098933,"text":"ofr20141061 - 2014 - Particle-tracking investigation of the retention of sucker larvae emerging from spawning grounds in Upper Klamath Lake, Oregon","interactions":[],"lastModifiedDate":"2014-06-19T13:11:03","indexId":"ofr20141061","displayToPublicDate":"2014-06-19T12:56:00","publicationYear":"2014","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":"2014-1061","title":"Particle-tracking investigation of the retention of sucker larvae emerging from spawning grounds in Upper Klamath Lake, Oregon","docAbstract":"This study had two objectives: (1) to use the results of an individual-based particle-tracking model of larval sucker dispersal through the Williamson River delta and Upper Klamath Lake, Oregon, to interpret field data collected throughout Upper Klamath and Agency Lakes, and (2) to use the model to investigate the retention of sucker larvae in the system as a function of Williamson River flow, wind, and lake elevation. This is a follow-up study to work reported in Wood and others (2014) in which the hydrodynamic model of Upper Klamath Lake was combined with an individual-based, particle-tracking model of larval fish entering the lake from spawning areas in the Williamson River. In the previous study, the performance of the model was evaluated through comparison with field data comprising larval sucker distribution collected in 2009 by The Nature Conservancy, Oregon State University (OSU), and the U.S. Geological Survey, primarily from the (at that time) recently reconnected Williamson River Delta and along the eastern shoreline of Upper Klamath Lake, surrounding the old river mouth. The previous study demonstrated that the validation of the model with field data was moderately successful and that the model was useful for describing the broad patterns of larval dispersal from the river, at least in the areas surrounding the river channel immediately downstream of the spawning areas and along the shoreline where larvae enter the lake.
\nIn this study, field data collected by OSU throughout the main body of Upper Klamath Lake, and not just around the Williamson River Delta, were compared to model simulation results. Because the field data were collected throughout the lake, it was necessary to include in the simulations larvae spawned at eastern shoreline springs that were not included in the earlier studies. A complicating factor was that the OSU collected data throughout the main body of the lake in 2011 and 2012, after the end of several years of larval drift collection in the Williamson River by the U.S. Geological Survey. Those larval drift data provided necessary boundary-condition information for the earlier studies, but there were no measured boundary conditions for larval input into model simulations during the years of this study (2011−12). Therefore, we developed a method to estimate a time series of larval drift in the Williamson River, and of the emergence of larvae from the gravel at the eastern shoreline springs, that captured the approximate timing of the larval pulse of the Lost River sucker (Deltistes luxatus) and shortnose sucker (Chasmistes brevirostris) and the relative magnitude of the pulses by species and spawning location. The method is not able to predict larval drift on any given day, but it can reasonably predict the approximate temporal progression of the larval drift through the season, based on counts of adult suckers returning to spawn. The accuracy in the timing of the larval pulses is not better than about plus or minus 5 days.
\nModel results and field data were consistent in the basic progression of both catch per unit effort (CPUE) and larval length through time. The model simulation results also duplicated some of the characteristics of the spatial patterns of density in the field data, notably the tendency for high larval densities closer to the eastern and western shorelines. However, the model simulations could not explain high densities in the northern part of the lake or far into Ball Bay, locations that are far from the source of larvae in the Williamson River or eastern shoreline springs (as measured along the predominant transport pathways simulated in the model). This suggests the possibility of unaccounted-for spawning areas in the northern part of the lake and also that the period during which larvae are transported passively by the currents is shorter than the 46 days simulated in the model. Similarly, the progression of larval lengths in the field data is not a simple progression from smaller to larger fish away from sources in the river and springs, as simulated by the particle-tracking model; the smallest fish were caught at different times near the Williamson River, in the northwestern part of the lake, and in the southernmost part of the lake. This again suggests that fish may be spawning at places other than the river and eastern springs, that our understanding of larval transport is incomplete, or both.
\nThe model was used to run 96 numerical “experiments” in which lake elevation, river discharge, and wind forcing were varied systematically in order to investigate the sensitivity of particle retention to each variable, and with particular emphasis on the idea of managing lake elevation to control emigration. The estimates of particle retention cannot be equated directly to retention of fish larvae, primarily because there was no mortality included in the simulations, but the relative comparison of retention and emigration around the matrix of experimental conditions provided several “big picture” results:
\n - Variables that cannot be controlled—winds and discharge—had the largest effect on retention. For example, at the lowest river discharge (20 cubic meters per second), simulated retention was high regardless of wind or lake elevation, whereas at the highest river discharge (100 cubic meters per second), retention was low regardless of wind or lake elevation.
\n - When river discharge and wind were held constant, a higher elevation delayed the onset of the most rapid exit of particles by 1 (from the springs) to 4 (from the river) days, but did not determine overall retention. Only under the combination of conditions consisting of low discharge (50 cubic meters per second or less) and strong wind reversals for several days was there a consistent effect of lake elevation on overall retention several weeks into the simulation, and, under those conditions, retention was at the high end of the possible range regardless of lake elevation.
\n - Under most combinations of conditions tested, after particles had been in the system for several days, the complex interaction between wind, elevation, and river discharge resulted in particle pathways, and therefore retention, being highly variable and unpredictable, at which point controlling lake elevation could not produce a predictable result. Therefore, on the basis of the model predictions, managing lake elevation probably is not a way to reliably provide any particular level of retention.
Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Oklahoma, elevation data are critical for flood risk management, infrastructure and construction management, agriculture and precision farming, natural resources conservation, wildlife and habitat management, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of local, State, and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.
\nThe National Enhanced Elevation Assessment (NEEA; Dewberry, 2011) evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.
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Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":494479,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70104185,"text":"sir20145078 - 2014 - Estimation of flood discharges at selected annual exceedance probabilities for unregulated, rural streams in Vermont, with a section on Vermont regional skew regression","interactions":[],"lastModifiedDate":"2014-06-19T11:15:42","indexId":"sir20145078","displayToPublicDate":"2014-06-19T11:06:00","publicationYear":"2014","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":"2014-5078","title":"Estimation of flood discharges at selected annual exceedance probabilities for unregulated, rural streams in Vermont, with a section on Vermont regional skew regression","docAbstract":"This report provides estimates of flood discharges at selected annual exceedance probabilities (AEPs) for streamgages in and adjacent to Vermont and equations for estimating flood discharges at AEPs of 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent (recurrence intervals of 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-years, respectively) for ungaged, unregulated, rural streams in Vermont. The equations were developed using generalized least-squares regression. Flood-frequency and drainage-basin characteristics from 145 streamgages were used in developing the equations. The drainage-basin characteristics used as explanatory variables in the regression equations include drainage area, percentage of wetland area, and the basin-wide mean of the average annual precipitation. The average standard errors of prediction for estimating the flood discharges at the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent AEP with these equations are 34.9, 36.0, 38.7, 42.4, 44.9, 47.3, 50.7, and 55.1 percent, respectively.
\nFlood discharges at selected AEPs for streamgages were computed by using the Expected Moments Algorithm. To improve estimates of the flood discharges for given exceedance probabilities at streamgages in Vermont, a new generalized skew coefficient was developed. The new generalized skew for the region is a constant, 0.44. The mean square error of the generalized skew coefficient is 0.078. This report describes a technique for using results from the regression equations to adjust an AEP discharge computed from a streamgage record. This report also describes a technique for using a drainage-area adjustment to estimate flood discharge at a selected AEP for an ungaged site upstream or downstream from a streamgage.
\nThe final regression equations and the flood-discharge frequency data used in this study will be available in StreamStats. StreamStats is a World Wide Web application providing automated regression-equation solutions for user-selected sites on streams.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145078","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Olson, S.A., and with a section by Veilleux, A.G., 2014, Estimation of flood discharges at selected annual exceedance probabilities for unregulated, rural streams in Vermont, with a section on Vermont regional skew regression: U.S. Geological Survey Scientific Investigations Report 2014-5078, Report: vi, 27 p.; Appendixes 1-8, 7, 9, https://doi.org/10.3133/sir20145078.","productDescription":"Report: vi, 27 p.; Appendixes 1-8, 7, 9","numberOfPages":"37","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-052679","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":288898,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145078.jpg"},{"id":288893,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5078/"},{"id":288894,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5078/pdf/sir2014-5078.pdf"},{"id":288895,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5078/appendix/sir2014-5078_olson_apend01-08.xlsx"},{"id":288897,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5078/appendix/sir2014-5078_olson_apend09.xlsx"},{"id":288896,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5078/appendix/sir2014-5078_olson_apend07.pdf"}],"country":"United States","state":"Vermont","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -74.7537,42.1919 ], [ -74.7537,45.5564 ], [ -70.5267,45.5564 ], [ -70.5267,42.1919 ], [ -74.7537,42.1919 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae76aae4b0abf75cf2bfd6","contributors":{"authors":[{"text":"Olson, Scott A. 0000-0002-1064-2125 solson@usgs.gov","orcid":"https://orcid.org/0000-0002-1064-2125","contributorId":2059,"corporation":false,"usgs":true,"family":"Olson","given":"Scott","email":"solson@usgs.gov","middleInitial":"A.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493625,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"with a section by Veilleux, Andrea G.","contributorId":74302,"corporation":false,"usgs":true,"family":"with a section by Veilleux","given":"Andrea","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":493626,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70189943,"text":"70189943 - 2014 - Modeling low-temperature geochemical processes:","interactions":[],"lastModifiedDate":"2022-12-09T16:44:03.209979","indexId":"70189943","displayToPublicDate":"2014-06-19T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"7.2","title":"Modeling low-temperature geochemical processes:","docAbstract":"This chapter provides an overview of geochemical modeling that applies to water–rock interactions under ambient conditions of temperature and pressure. Topics include modeling definitions, historical background, issues of activity coefficients, popular codes and databases, examples of modeling common types of water–rock interactions, and issues of model reliability. Examples include speciation, microbial redox kinetics and ferrous iron oxidation, calcite dissolution, pyrite oxidation, combined pyrite and calcite dissolution, dedolomitization, seawater–carbonate groundwater mixing, reactive-transport modeling in streams, modeling catchments, and evaporation of seawater. The chapter emphasizes limitations to geochemical modeling: that a proper understanding and ability to communicate model results well are as important as completing a set of useful modeling computations and that greater sophistication in model and code development is not necessarily an advancement. If the goal is to understand how a particular geochemical system behaves, it is better to collect more field data than rely on computer codes.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Reference module in earth systems and environmental sciences: Treatise on geochemistry","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/B978-0-08-095975-7.00502-7","usgsCitation":"Nordstrom, D.K., and Campbell, K.M., 2014, Modeling low-temperature geochemical processes:, chap. 7.2 of Reference module in earth systems and environmental sciences: Treatise on geochemistry, v. 7, p. 27-68, https://doi.org/10.1016/B978-0-08-095975-7.00502-7.","productDescription":"42 p.","startPage":"27","endPage":"68","ipdsId":"IP-038052","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":345118,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","edition":"2nd Edition","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"599fe5bce4b038630d022110","contributors":{"authors":[{"text":"Nordstrom, D. Kirk 0000-0003-3283-5136 dkn@usgs.gov","orcid":"https://orcid.org/0000-0003-3283-5136","contributorId":749,"corporation":false,"usgs":true,"family":"Nordstrom","given":"D.","email":"dkn@usgs.gov","middleInitial":"Kirk","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":false,"id":706839,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Campbell, Kate M. 0000-0002-8715-5544 kcampbell@usgs.gov","orcid":"https://orcid.org/0000-0002-8715-5544","contributorId":1441,"corporation":false,"usgs":true,"family":"Campbell","given":"Kate","email":"kcampbell@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":706840,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70187705,"text":"70187705 - 2014 - A mapping and monitoring assessment of the Philippines' mangrove forests from 1990 to 2010","interactions":[],"lastModifiedDate":"2017-05-15T14:44:11","indexId":"70187705","displayToPublicDate":"2014-06-19T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"A mapping and monitoring assessment of the Philippines' mangrove forests from 1990 to 2010","docAbstract":"Information on the present condition and spatiotemporal dynamics of mangrove forests is needed for land-change studies and integrated natural resources planning and management. Although several national mangrove estimates for the Philippines exist, information is unavailable at sufficient spatial and thematic detail for change analysis. Historical and contemporary mangrove distribution maps of the Philippines for 1990 and 2010 were prepared at nominal 30-m spatial resolution using Landsat satellite data. Image classification was performed using a supervised decision tree classification approach. Additionally, decadal land-cover change maps from 1990 to 2010 were prepared to depict changes in mangrove area. Total mangrove area decreased 10.5% from 1990 to 2010. Comparison of estimates produced from this study with selected historical mangrove area estimates revealed that total mangrove area decreased by approximately half (51.8%) from 1918 to 2010. This study provides the most current and reliable data regarding the Philippines mangrove area and spatial distribution and delineates where and when mangrove change has occurred in recent decades. The results from this study are useful for developing conservation strategies, biodiversity loss mitigation efforts, and future monitoring and analysis.
","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/JCOASTRES-D-13-00057.1","usgsCitation":"Long, J., Napton, D., Giri, C., and Graesser, J., 2014, A mapping and monitoring assessment of the Philippines' mangrove forests from 1990 to 2010: Journal of Coastal Research, v. 30, no. 2, p. 260-271, https://doi.org/10.2112/JCOASTRES-D-13-00057.1.","productDescription":"12 p.","startPage":"260","endPage":"271","ipdsId":"IP-046144","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":341308,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Phillippines","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[126.37681,8.41471],[126.47851,7.75035],[126.53742,7.18938],[126.19677,6.27429],[125.83142,7.29372],[125.36385,6.78649],[125.68316,6.04966],[125.39651,5.581],[124.21979,6.16136],[123.93872,6.88514],[124.24366,7.36061],[123.61021,7.83353],[123.29607,7.41888],[122.82551,7.45737],[122.0855,6.89942],[121.91993,7.19212],[122.31236,8.03496],[122.9424,8.31624],[123.48769,8.69301],[123.84115,8.24032],[124.60147,8.51416],[124.76461,8.96041],[125.47139,8.987],[125.41212,9.76033],[126.22271,9.28607],[126.30664,8.78249],[126.37681,8.41471]]],[[[123.98244,10.27878],[123.62318,9.95009],[123.30992,9.31827],[122.99588,9.02219],[122.38005,9.71336],[122.58609,9.98104],[122.83708,10.26116],[122.94741,10.88187],[123.49885,10.94062],[123.33777,10.26738],[124.07794,11.23273],[123.98244,10.27878]]],[[[118.50458,9.31638],[117.17427,8.3675],[117.66448,9.06689],[118.38691,9.6845],[118.98734,10.37629],[119.5115,11.36967],[119.68968,10.55429],[119.02946,10.00365],[118.50458,9.31638]]],[[[121.88355,11.89176],[122.48382,11.58219],[123.12022,11.58366],[123.10084,11.16593],[122.63771,10.74131],[122.00261,10.44102],[121.96737,10.90569],[122.03837,11.41584],[121.88355,11.89176]]],[[[125.50255,12.16269],[125.78346,11.04612],[125.01188,11.31145],[125.03276,10.97582],[125.27745,10.35872],[124.80182,10.13468],[124.76017,10.838],[124.4591,10.88993],[124.30252,11.49537],[124.89101,11.41558],[124.87799,11.79419],[124.26676,12.55776],[125.22712,12.53572],[125.50255,12.16269]]],[[[121.52739,13.06959],[121.26219,12.20556],[120.8339,12.7045],[120.32344,13.46641],[121.18013,13.4297],[121.52739,13.06959]]],[[[121.32131,18.50406],[121.9376,18.21855],[122.24601,18.47895],[122.33696,18.22488],[122.17428,17.81028],[122.51565,17.0935],[122.25231,16.26244],[121.66279,15.93102],[121.50507,15.12481],[121.72883,14.32838],[122.25893,14.2182],[122.70128,14.33654],[123.9503,13.78213],[123.85511,13.23777],[124.18129,12.99753],[124.07742,12.53668],[123.29804,13.02753],[122.92865,13.55292],[122.67136,13.18584],[122.03465,13.78448],[121.12638,13.63669],[120.62864,13.85766],[120.67938,14.27102],[120.99182,14.52539],[120.69334,14.75667],[120.56415,14.39628],[120.07043,14.97087],[119.92093,15.40635],[119.88377,16.3637],[120.28649,16.03463],[120.39005,17.59908],[120.71587,18.50523],[121.32131,18.50406]]]]},\"properties\":{\"name\":\"Philippines\"}}]}","volume":"30","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"591abe38e4b0a7fdb43c8bfb","contributors":{"authors":[{"text":"Long, Jordan 0000-0002-4814-464X jlong@usgs.gov","orcid":"https://orcid.org/0000-0002-4814-464X","contributorId":3609,"corporation":false,"usgs":true,"family":"Long","given":"Jordan","email":"jlong@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":695185,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Napton, Darrell","contributorId":176288,"corporation":false,"usgs":false,"family":"Napton","given":"Darrell","affiliations":[],"preferred":false,"id":695186,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Giri, Chandra cgiri@usgs.gov","contributorId":189128,"corporation":false,"usgs":true,"family":"Giri","given":"Chandra","email":"cgiri@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":695184,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graesser, Jordan","contributorId":192030,"corporation":false,"usgs":false,"family":"Graesser","given":"Jordan","email":"","affiliations":[],"preferred":false,"id":695189,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70112913,"text":"sir20145073 - 2014 - Streamflow, water quality, and aquatic macroinvertebrates of selected streams in Fairfax County, Virginia, 2007-12","interactions":[],"lastModifiedDate":"2014-06-18T15:06:54","indexId":"sir20145073","displayToPublicDate":"2014-06-18T15:01:00","publicationYear":"2014","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":"2014-5073","title":"Streamflow, water quality, and aquatic macroinvertebrates of selected streams in Fairfax County, Virginia, 2007-12","docAbstract":"Efforts to mitigate the effects of urbanization on streams rely on best management practices (BMPs) that are implemented with the intent of reducing and retaining stormwater runoff. A cooperative monitoring effort between the U.S. Geological Survey and Fairfax County, Virginia, was initiated in 2007 to assess the condition of county streams and document watershed-scale responses to the implementation of BMPs. Assessment of the data collected during the first 5 years of this monitoring program focused on characterizing the hydrologic and ecological condition of 14 monitored streams.
\nHydrologic, chemical, and macroinvertebrate community conditions in the streams monitored were found to be consistent, overall, with conditions commonly observed in urban streams. Hydrologically, the monitored streams were found to be flashy, with flashiness positively related to road cover in the watershed. Typical pH values of streams throughout the network centered around neutrality (pH = 7) with strong daily fluctuations apparent in the continuous data. Patterns in specific conductance were largely representative of anthropogenic disturbances—watersheds having the greatest percentage of open space and estate residential land-use had the lowest typical specific conductance values, and specific conductance variability was less than what is observed in watersheds that are more intensively developed. In watersheds having greater road coverage, and more development in general, increases in specific conductance over several orders of magnitude were observed during winter months as a result of the application of de-icing salts on impervious surfaces. Dissolved oxygen conditions were typically within the range required to support healthy biological communities, although occasional departures during summer months at some sites fell below the impairment threshold for streams in Virginia.
\nNitrogen (N) and phosphorus (P), concentration patterns were largely consistent across the network, with few exceptions. Nitrogen concentrations in monthly samples were generally low and dominated by nitrate. Exceptions to the generally low N concentrations occurred at Captain Hickory Run, which had a median total N concentration of approximately 4.9 milligrams per liter (mg/L), compared to the network-wide median of approximately 1.7 mg/L, and at Popes Head Creek Tributary, where total N concentrations spiked to 6–8 mg/L during low-flow periods in August or September of each year. Phosphorus concentrations in monthly samples were generally low and dominated by the dissolved fraction. Two monitoring stations in the network, Flatlick Branch and Frog Branch, are notable for having median total P concentrations that were, on average, approximately three times greater than the median total P concentration of 0.02 mg/L observed at the other 12 stations in the network.
\nSuspended-sediment and nutrient loads and yields were similar to those of urbanized watersheds in other studies, although the yields from these urbanized basins were greater than, or within, the upper quartile of yields observed throughout the Chesapeake Bay watershed. Annual suspended-sediment loads ranged from 289–10,275 tons, with a median of 1,311 tons, and corresponding yields ranged from 107–2,827 tons per square mile (ton/mi2), with a median of 277 ton/mi2. Annual total N loads ranged from 8,014–36,413 pounds, with a median of 21,314 pounds, and corresponding yields ranged from 3,361–8,360 pounds per square mile (lb/mi2), with a median of 6,200 lb/mi2. Annual total P loads ranged from 380–6,558 pounds, with a median of 1,874 pounds, and corresponding yields ranged from 140–1,562 lb/mi2, with a median of 543 lb/mi2.
\nBenthic macroinvertebrate community metrics indicated that streams throughout Fairfax County are generally of poor health. One station, Castle Creek, was an exception with results indicating relatively high quality aquatic health.
\nSix additional monitoring stations were added to the network in 2012 to improve spatial coverage throughout Fairfax County. Monitoring activities are expected to continue at all 20 stations for the foreseeable future as BMP implementation is conducted.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145073","issn":"2328-0328","isbn":"978-1-4113-3788-6","collaboration":"Prepared in cooperation with Fairfax County, Virginia","usgsCitation":"Jastram, J.D., 2014, Streamflow, water quality, and aquatic macroinvertebrates of selected streams in Fairfax County, Virginia, 2007-12: U.S. Geological Survey Scientific Investigations Report 2014-5073, x, 68 p., https://doi.org/10.3133/sir20145073.","productDescription":"x, 68 p.","numberOfPages":"82","onlineOnly":"N","temporalStart":"2007-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-051336","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":288839,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145073.jpg"},{"id":288837,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5073/"},{"id":288838,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5073/pdf/sir2014-5073.pdf"}],"scale":"2000000","country":"United States","state":"Virginia","county":"Fairfax County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -77.5,38.666667 ], [ -77.5,39.0 ], [ -77.0,39.0 ], [ -77.0,38.666667 ], [ -77.5,38.666667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae7843e4b0abf75cf2cf70","contributors":{"authors":[{"text":"Jastram, John D. 0000-0002-9416-3358 jdjastra@usgs.gov","orcid":"https://orcid.org/0000-0002-9416-3358","contributorId":3531,"corporation":false,"usgs":true,"family":"Jastram","given":"John","email":"jdjastra@usgs.gov","middleInitial":"D.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494913,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70095721,"text":"ds829 - 2014 - Archive of digital chirp subbottom profile data collected during USGS Cruise 13GFP01, Brownlee Dam and Hells Canyon Reservoir, Idaho and Oregon, 2013","interactions":[],"lastModifiedDate":"2014-06-18T14:43:21","indexId":"ds829","displayToPublicDate":"2014-06-18T14:37:00","publicationYear":"2014","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":"829","title":"Archive of digital chirp subbottom profile data collected during USGS Cruise 13GFP01, Brownlee Dam and Hells Canyon Reservoir, Idaho and Oregon, 2013","docAbstract":"From March 16 - 31, 2013, the U.S. Geological Survey in cooperation with the Idaho Power Company conducted a geophysical survey to investigate sediment deposits and long-term sediment transport within the Snake River from Brownlee Dam to Hells Canyon Reservoir, along the Idaho and Oregon border; this effort will help the USGS to better understand geologic processes. This report serves as an archive of unprocessed digital chirp subbottom data, trackline maps, navigation files, Geographic Information System (GIS) files, Field Activity Collection System (FACS) logs, and formal Federal Geographic Data Committee (FGDC) metadata. Gained (showing a relative increase in signal amplitude) digital images of the seismic profiles are also provided. Refer to the Acronyms page for expansions of acronyms and abbreviations used in this report.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds829","issn":"2327-638X","collaboration":"Idaho Power Company, Boise, ID","usgsCitation":"Forde, A.S., Dadisman, S.V., Flocks, J.G., Fosness, R.L., Welcker, C., and Kelso, K.W., 2014, Archive of digital chirp subbottom profile data collected during USGS Cruise 13GFP01, Brownlee Dam and Hells Canyon Reservoir, Idaho and Oregon, 2013: U.S. Geological Survey Data Series 829, Report: HTML document; Downloads directory, https://doi.org/10.3133/ds829.","productDescription":"Report: HTML document; Downloads directory","onlineOnly":"N","temporalStart":"2013-03-16","temporalEnd":"2013-03-31","ipdsId":"IP-053170","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":288834,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds829.jpg"},{"id":288833,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0829/downloads"},{"id":288831,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0829/"},{"id":288832,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0829/title.html"}],"country":"United States","state":"Idaho;Oregon","otherGeospatial":"Brownlee Dam;Hells Canyon Reservoir","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.0,43.5 ], [ -119.0,45.0 ], [ -117.5,45.0 ], [ -117.5,43.5 ], [ -119.0,43.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae7630e4b0abf75cf2bebf","contributors":{"authors":[{"text":"Forde, Arnell S. 0000-0002-5581-2255 aforde@usgs.gov","orcid":"https://orcid.org/0000-0002-5581-2255","contributorId":376,"corporation":false,"usgs":true,"family":"Forde","given":"Arnell","email":"aforde@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":491382,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dadisman, Shawn V. sdadisman@usgs.gov","contributorId":2207,"corporation":false,"usgs":true,"family":"Dadisman","given":"Shawn","email":"sdadisman@usgs.gov","middleInitial":"V.","affiliations":[],"preferred":true,"id":491384,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flocks, James G. 0000-0002-6177-7433 jflocks@usgs.gov","orcid":"https://orcid.org/0000-0002-6177-7433","contributorId":816,"corporation":false,"usgs":true,"family":"Flocks","given":"James","email":"jflocks@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":491383,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fosness, Ryan L. 0000-0003-4089-2704 rfosness@usgs.gov","orcid":"https://orcid.org/0000-0003-4089-2704","contributorId":2703,"corporation":false,"usgs":true,"family":"Fosness","given":"Ryan","email":"rfosness@usgs.gov","middleInitial":"L.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":491385,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Welcker, Chris","contributorId":63314,"corporation":false,"usgs":true,"family":"Welcker","given":"Chris","email":"","affiliations":[],"preferred":false,"id":491387,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kelso, Kyle W. 0000-0003-0615-242X kkelso@usgs.gov","orcid":"https://orcid.org/0000-0003-0615-242X","contributorId":4307,"corporation":false,"usgs":true,"family":"Kelso","given":"Kyle","email":"kkelso@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":491386,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70112920,"text":"70112920 - 2014 - The response of stream periphyton to Pacific salmon: using a model to understand the role of environmental context","interactions":[],"lastModifiedDate":"2014-06-18T13:43:10","indexId":"70112920","displayToPublicDate":"2014-06-18T13:39:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"The response of stream periphyton to Pacific salmon: using a model to understand the role of environmental context","docAbstract":"1. In stream ecosystems, Pacific salmon deliver subsidies of marine-derived nutrients and disturb the stream bed during spawning. The net effect of this nutrient subsidy and physical disturbance on biological communities can be hard to predict and is likely to be mediated by environmental conditions. For periphyton, empirical studies have revealed that the magnitude and direction of the response to salmon varies from one location to the next. Salmon appear to increase periphyton biomass and/or production in some contexts (a positive response), but decrease them in others (a negative response).
\n2. To reconcile these seemingly conflicting results, we constructed a system dynamics model that links periphyton biomass and production to salmon spawning. We used this model to explore how environmental conditions influence the periphyton response to salmon.
\n3. Our simulations suggest that the periphyton response to salmon is strongly mediated by both background nutrient concentrations and the proportion of the stream bed suitable for spawning. Positive periphyton responses occurred when both background nutrient concentrations were low (nutrient limiting conditions) and when little of the stream bed was suitable for spawning (because the substratum is too coarse). In contrast, negative responses occurred when nutrient concentrations were higher or a larger proportion of the bed was suitable for spawning.
\n4. Although periphyton biomass generally remained above or below background conditions for several months following spawning, periphyton production returned quickly to background values shortly afterwards. As a result, based upon our simulations, salmon did not greatly increase or decrease overall annual periphyton production. This suggests that any increase in production by fish or invertebrates in response to returning salmon is more likely to occur via direct consumption of salmon carcasses and/or eggs, rather than the indirect effects of greater periphyton production.
\n5. Overall, our simulations suggest that environmental factors need to be taken into account when considering the effects of spawning salmon on aquatic ecosystems. Our model offers researchers a framework for testing periphyton response to salmon across a range of conditions, which can be used to generate hypotheses, plan field experiments and guide data collection.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Freshwater Biology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/fwb.12356","usgsCitation":"Bellmore, J.R., Fremier, A., Mejia, F., and Newsom, M., 2014, The response of stream periphyton to Pacific salmon: using a model to understand the role of environmental context: Freshwater Biology, v. 59, no. 7, p. 1437-1451, https://doi.org/10.1111/fwb.12356.","productDescription":"15 p.","startPage":"1437","endPage":"1451","numberOfPages":"15","ipdsId":"IP-051251","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":288822,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288801,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/fwb.12356"}],"volume":"59","issue":"7","noUsgsAuthors":false,"publicationDate":"2014-03-17","publicationStatus":"PW","scienceBaseUri":"53ae7870e4b0abf75cf2d4e3","contributors":{"authors":[{"text":"Bellmore, J. Ryan","contributorId":104790,"corporation":false,"usgs":true,"family":"Bellmore","given":"J.","email":"","middleInitial":"Ryan","affiliations":[],"preferred":false,"id":494932,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fremier, Alexander K.","contributorId":104403,"corporation":false,"usgs":true,"family":"Fremier","given":"Alexander K.","affiliations":[],"preferred":false,"id":494931,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mejia, Francine","contributorId":106804,"corporation":false,"usgs":true,"family":"Mejia","given":"Francine","affiliations":[],"preferred":false,"id":494933,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Newsom, Michael","contributorId":16753,"corporation":false,"usgs":true,"family":"Newsom","given":"Michael","affiliations":[],"preferred":false,"id":494930,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70095563,"text":"sir20145032 - 2014 - Simulation of the effects of rainfall and groundwater use on historical lake water levels, groundwater levels, and spring flows in central Florida","interactions":[],"lastModifiedDate":"2014-06-18T12:47:57","indexId":"sir20145032","displayToPublicDate":"2014-06-18T12:42:00","publicationYear":"2014","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":"2014-5032","title":"Simulation of the effects of rainfall and groundwater use on historical lake water levels, groundwater levels, and spring flows in central Florida","docAbstract":"The urbanization of central Florida has progressed substantially in recent decades, and the total population in Lake, Orange, Osceola, Polk, and Seminole Counties more than quadrupled from 1960 to 2010. The Floridan aquifer system is the primary source of water for potable, industrial, and agricultural purposes in central Florida. Despite increases in groundwater withdrawals to meet the demand of population growth, recharge derived by infiltration of rainfall in the well-drained karst terrain of central Florida is the largest component of the long-term water balance of the Floridan aquifer system. To complement existing physics-based groundwater flow models, artificial neural networks and other data-mining techniques were used to simulate historical lake water level, groundwater level, and spring flow at sites throughout the area.
\nHistorical data were examined using descriptive statistics, cluster analysis, and other exploratory analysis techniques to assess their suitability for more intensive data-mining analysis. Linear trend analyses of meteorological data collected by the National Oceanic and Atmospheric Administration at 21 sites indicate 67 percent of sites exhibited upward trends in air temperature over at least a 45-year period of record, whereas 76 percent exhibited downward trends in rainfall over at least a 95-year period of record. Likewise, linear trend analyses of hydrologic response data, which have varied periods of record ranging in length from 10 to 79 years, indicate that water levels in lakes (307 sites) were about evenly split between upward and downward trends, whereas water levels in 69 percent of wells (out of 455 sites) and flows in 68 percent of springs (out of 19 sites) exhibited downward trends. Total groundwater use in the study area increased from about 250 million gallons per day (Mgal/d) in 1958 to about 590 Mgal/d in 1980 and remained relatively stable from 1981 to 2008, with a minimum of 559 Mgal/d in 1994 and a maximum of 773 Mgal/d in 2000. The change in groundwater-use trend in the early 1980s and the following period of relatively slight trend is attributable to the concomitant effects of increasing public-supply withdrawals and decreasing use of water by the phosphate industry and agriculture.
\nOn the basis of available historical data and exploratory analyses, empirical lake water-level, groundwater-level, and spring-flow models were developed for 22 lakes, 23 wells, and 6 springs. Input time series consisting of various frequencies and frequency-band components of daily rainfall (1942 to 2008) and monthly total groundwater use (1957 to 2008) resulted in hybrid signal-decomposition artificial neural network models. The final models explained much of the variability in observed hydrologic data, with 43 of the 51 sites having coefficients of determination exceeding 0.6, and the models matched the magnitude of the observed data reasonably well, such that models for 32 of the 51 sites had root-mean-square errors less than 10 percent of the measured range of the data. The Central Florida Artificial Neural Network Decision Support System was developed to integrate historical databases and the 102 site-specific artificial neural network models, model controls, and model output into a spreadsheet application with a graphical user interface that allows the user to simulate scenarios of interest.
\nOverall, the data-mining analyses indicate that the Floridan aquifer system in central Florida is a highly conductive, dynamic, open system that is strongly influenced by external forcing. The most important external forcing appears to be rainfall, which explains much of the multiyear cyclic variability and long-term downward trends observed in lake water levels, groundwater levels, and spring flows. For most sites, groundwater use explains less of the observed variability in water levels and flows than rainfall. Relative groundwater-use impacts are greater during droughts, however, and long-term trends in water levels and flows were identified that are consistent with historical groundwater-use patterns. The sensitivity of the hydrologic system to rainfall is expected, owing to the well-drained karst terrain and relatively thin confinement of the Floridan aquifer system in much of central Florida. These characteristics facilitate the relatively rapid transmission of infiltrating water from rainfall to the water table and contribute to downward leakage of water to the Floridan aquifer system. The areally distributed nature of rainfall, as opposed to the site-specific nature of groundwater use, and the generally high transmissivity and low storativity properties of the semiconfined Floridan aquifer system contribute to the prevalence of water-level and flow patterns that mimic rainfall patterns. In general, the data-mining analyses demonstrate that the hydrologic system in central Florida is affected by groundwater use differently during wet periods, when little or no system storage is available (high water levels), compared to dry periods, when there is excess system storage (low water levels). Thus, by driving the overall behavior of the system, rainfall indirectly influences the degree to which groundwater use will effect persistent trends in water levels and flows, with groundwater-use impacts more prevalent during periods of low water levels and spring flows caused by low rainfall and less prevalent during periods of high water levels and spring flows caused by high rainfall. Differences in the magnitudes of rainfall and groundwater use during wet and dry periods also are important determinants of hydrologic response.
\nAn important implication of the data-mining analyses is that rainfall variability at subannual to multidecadal timescales must be considered in combination with groundwater use to provide robust system-response predictions that enhance sustainable resource management in an open karst aquifer system. The data-driven approach was limited, however, by the confounding effects of correlation between rainfall and groundwater use, the quality and completeness of the historical databases, and the spatial variations in groundwater use. The data-mining analyses indicate that available historical data when used alone do not contain sufficient information to definitively quantify the related individual effects of rainfall and groundwater use on hydrologic response. The knowledge gained from data-driven modeling and the results from physics-based modeling, when compared and used in combination, can yield a more comprehensive assessment and a more robust understanding of the hydrologic system than either of the approaches used separately.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145032","issn":"2328-0328","collaboration":"Prepared in cooperation with the St. Johns River Water Management District, Southwest Florida Water Management District, and South Florida Water Management District","usgsCitation":"O’Reilly, A.M., Roehl, E.A., Conrads, P., Daamen, R.C., and Petkewich, M.D., 2014, Simulation of the effects of rainfall and groundwater use on historical lake water levels, groundwater levels, and spring flows in central Florida: U.S. Geological Survey Scientific Investigations Report 2014-5032, Report: xi, 153 p.; Appendix 1: ZIP; Appendix 2: XLSX; Appendix 3: PDF; Appendix 6: ZIP; Appendix 7: XLSX, https://doi.org/10.3133/sir20145032.","productDescription":"Report: xi, 153 p.; Appendix 1: ZIP; Appendix 2: XLSX; Appendix 3: PDF; Appendix 6: ZIP; Appendix 7: XLSX","numberOfPages":"169","onlineOnly":"Y","ipdsId":"IP-049051","costCenters":[{"id":285,"text":"Florida Water Science Center","active":false,"usgs":true}],"links":[{"id":288816,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145032.jpg"},{"id":288811,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5032/appendix/sir2014-5032_appendix1-v2.5.zip"},{"id":288812,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5032/appendix/sir2014-5032_appendix2-gudv.xlsx"},{"id":288809,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5032/"},{"id":288810,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5032/pdf/sir2014-5032.pdf"},{"id":288813,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5032/appendix/sir2014-5032_appendix3_tableA3-1.pdf"},{"id":288814,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5032/appendix/sir2014-5032_appendix6-cfann-dss20120924.zip"},{"id":288815,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5032/appendix/sir2014-5032_appendix7-mdv.xlsx"}],"projection":"Universal Transverse Mercator projection","country":"United States","state":"Florida","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -82.0,28.0 ], [ -82.0,29.0 ], [ -81.0,29.0 ], [ -81.0,28.0 ], [ -82.0,28.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae782ce4b0abf75cf2ccb3","contributors":{"authors":[{"text":"O’Reilly, Andrew M. 0000-0003-3220-1248 aoreilly@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-1248","contributorId":2184,"corporation":false,"usgs":true,"family":"O’Reilly","given":"Andrew","email":"aoreilly@usgs.gov","middleInitial":"M.","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"preferred":true,"id":491298,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roehl, Edwin A. Jr.","contributorId":108083,"corporation":false,"usgs":false,"family":"Roehl","given":"Edwin","suffix":"Jr.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":491300,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conrads, Paul 0000-0003-0408-4208 pconrads@usgs.gov","orcid":"https://orcid.org/0000-0003-0408-4208","contributorId":764,"corporation":false,"usgs":true,"family":"Conrads","given":"Paul","email":"pconrads@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":491296,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daamen, Ruby C.","contributorId":105391,"corporation":false,"usgs":true,"family":"Daamen","given":"Ruby","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":491299,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Petkewich, Matthew D. 0000-0002-5749-6356 mdpetkew@usgs.gov","orcid":"https://orcid.org/0000-0002-5749-6356","contributorId":982,"corporation":false,"usgs":true,"family":"Petkewich","given":"Matthew","email":"mdpetkew@usgs.gov","middleInitial":"D.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":491297,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70110857,"text":"ds855 - 2014 - Mobile terrestrial light detection and ranging (T-LiDAR) survey of areas on Dauphin Island, Alabama, in the aftermath of Hurricane Isaac, 2012","interactions":[],"lastModifiedDate":"2014-06-18T09:32:54","indexId":"ds855","displayToPublicDate":"2014-06-18T09:16:00","publicationYear":"2014","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":"855","title":"Mobile terrestrial light detection and ranging (T-LiDAR) survey of areas on Dauphin Island, Alabama, in the aftermath of Hurricane Isaac, 2012","docAbstract":"Topographic survey data of areas on Dauphin Island on the Alabama coast were collected using a truck-mounted mobile terrestrial light detection and ranging system. This system is composed of a high frequency laser scanner in conjunction with an inertial measurement unit and a position and orientation computer to produce highly accurate topographic datasets. A global positioning system base station was set up on a nearby benchmark and logged vertical and horizontal position information during the survey for post-processing. Survey control points were also collected throughout the study area to determine residual errors. Data were collected 5 days after Hurricane Isaac made landfall in early September 2012 to document sediment deposits prior to clean-up efforts. Three data files in ASCII text format with the extension .xyz are included in this report, and each file is named according to both the acquisition date and the relative geographic location on Dauphin Island (for example, 20120903_Central.xyz). Metadata are also included for each of the files in both Extensible Markup Language with the extension .xml and ASCII text formats. These topographic data can be used to analyze the effects of storm surge on barrier island environments and also serve as a baseline dataset for future change detection analyses.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds855","issn":"2327-638X","usgsCitation":"Kimbrow, D.R., 2014, Mobile terrestrial light detection and ranging (T-LiDAR) survey of areas on Dauphin Island, Alabama, in the aftermath of Hurricane Isaac, 2012: U.S. Geological Survey Data Series 855, Report: HTML document; Downloads directory, https://doi.org/10.3133/ds855.","productDescription":"Report: HTML document; Downloads directory","onlineOnly":"Y","ipdsId":"IP-055484","costCenters":[{"id":105,"text":"Alabama Water Science Center","active":true,"usgs":true}],"links":[{"id":288755,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds855.gif"},{"id":288749,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0855/"},{"id":288753,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0855/title_page.html"},{"id":288754,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0855/Downloads"}],"country":"United States","state":"Alabama","otherGeospatial":"Dauphin Island","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.233333,30.216667 ], [ -88.233333,30.3 ], [ -88.083333,30.3 ], [ -88.083333,30.216667 ], [ -88.233333,30.216667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae777be4b0abf75cf2c147","contributors":{"authors":[{"text":"Kimbrow, Dustin R. dkimbrow@usgs.gov","contributorId":3915,"corporation":false,"usgs":true,"family":"Kimbrow","given":"Dustin","email":"dkimbrow@usgs.gov","middleInitial":"R.","affiliations":[{"id":105,"text":"Alabama Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494173,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70098143,"text":"ofr20141057 - 2014 - Histograms showing variations in oil yield, water yield, and specific gravity of oil from Fischer assay analyses of oil-shale drill cores and cuttings from the Piceance Basin, northwestern Colorado","interactions":[],"lastModifiedDate":"2014-06-18T09:03:04","indexId":"ofr20141057","displayToPublicDate":"2014-06-18T08:53:00","publicationYear":"2014","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":"2014-1057","title":"Histograms showing variations in oil yield, water yield, and specific gravity of oil from Fischer assay analyses of oil-shale drill cores and cuttings from the Piceance Basin, northwestern Colorado","docAbstract":"Recent studies indicate that the Piceance Basin in northwestern Colorado contains over 1.5 trillion barrels of oil in place, making the basin the largest known oil-shale deposit in the world. Previously published histograms display oil-yield variations with depth and widely correlate rich and lean oil-shale beds and zones throughout the basin. Histograms in this report display oil-yield data plotted alongside either water-yield or oil specific-gravity data. Fischer assay analyses of core and cutting samples collected from exploration drill holes penetrating the Eocene Green River Formation in the Piceance Basin can aid in determining the origins of those deposits, as well as estimating the amount of organic matter, halite, nahcolite, and water-bearing minerals. This report focuses only on the oil yield plotted against water yield and oil specific gravity.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141057","usgsCitation":"Dietrich, J.D., Brownfield, M.E., Johnson, R.C., and Mercier, T.J., 2014, Histograms showing variations in oil yield, water yield, and specific gravity of oil from Fischer assay analyses of oil-shale drill cores and cuttings from the Piceance Basin, northwestern Colorado: U.S. Geological Survey Open-File Report 2014-1057, Report: iii, 12p.; Downloads Directory, https://doi.org/10.3133/ofr20141057.","productDescription":"Report: iii, 12p.; Downloads Directory","numberOfPages":"15","onlineOnly":"Y","ipdsId":"IP-041055","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":288746,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141057.jpg"},{"id":288705,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1057/"},{"id":288742,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1057/pdf/ofr2014-1057.pdf"},{"id":288743,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1057/downloads/"}],"country":"United States","state":"Colorado","otherGeospatial":"Piceance Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -112.0,39.0 ], [ -112.0,43.0 ], [ -107.0,43.0 ], [ -107.0,39.0 ], [ -112.0,39.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae7738e4b0abf75cf2c0ad","contributors":{"authors":[{"text":"Dietrich, John D.","contributorId":53841,"corporation":false,"usgs":true,"family":"Dietrich","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":491636,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brownfield, Michael E. 0000-0003-3633-1138 mbrownfield@usgs.gov","orcid":"https://orcid.org/0000-0003-3633-1138","contributorId":1548,"corporation":false,"usgs":true,"family":"Brownfield","given":"Michael","email":"mbrownfield@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":491633,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Ronald C. 0000-0002-6197-5165 rcjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-6197-5165","contributorId":1550,"corporation":false,"usgs":true,"family":"Johnson","given":"Ronald","email":"rcjohnson@usgs.gov","middleInitial":"C.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":491634,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mercier, Tracey J. 0000-0002-8232-525X tmercier@usgs.gov","orcid":"https://orcid.org/0000-0002-8232-525X","contributorId":2847,"corporation":false,"usgs":true,"family":"Mercier","given":"Tracey","email":"tmercier@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":491635,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189761,"text":"70189761 - 2014 - The earthquake cycle in the San Francisco Bay region: A.D. 1600–2012","interactions":[],"lastModifiedDate":"2021-05-21T17:11:31.821686","indexId":"70189761","displayToPublicDate":"2014-06-18T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"The earthquake cycle in the San Francisco Bay region: A.D. 1600–2012","docAbstract":"Stress changes produced by the 1906 San Francisco earthquake had a profound effect on the seismicity of the San Francisco Bay region (SFBR), dramatically reducing it in the twentieth century. Whether the SFBR is still within or has emerged from this seismic quiescence is an issue of debate with implications for earthquake mechanics and seismic hazards. Historically, the SFBR has not experienced one complete earthquake cycle (i.e., the accumulation of stress, its release primarily as coseismic slip during surface‐faulting earthquakes, its re‐accumulation in the interval following, and its subsequent rerelease). The historical record of earthquake occurrence in the SFBR appears to be complete at about M 5.5 back to 1850 (Bakun, 1999). For large events, the record may be complete back to 1776, which represents about half a cycle. Paleoseismic data provide a more complete view of the most recent pre‐1906 SFBR earthquake cycle, extending it back to about 1600. Using these, we have developed estimates of magnitude and seismic moment for alternative sequences of surface‐faulting paleoearthquakes occurring between 1600 and 1776 on the region’s major faults. From these we calculate seismic moment and moment release rates for different time intervals between 1600 and 2012. These show the variability in moment release and suggest that, in the SFBR regional plate boundary, stress can be released on a single fault in great earthquakes such as that in 1906 and in multiple ruptures distributed on the regional plate boundary fault system on a decadal time scale.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120120322","usgsCitation":"Schwartz, D.P., Lienkaemper, J.J., Hecker, S., Kelson, K.I., Fumal, T.E., Baldwin, J.N., Seitz, G.G., and Niemi, T., 2014, The earthquake cycle in the San Francisco Bay region: A.D. 1600–2012: Bulletin of the Seismological Society of America, https://doi.org/10.1785/0120120322.","ipdsId":"IP-053346","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":344265,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122,\n 39\n ],\n [\n -120.5,\n 37.2\n ],\n [\n -122.1,\n 36.4\n ],\n [\n -123.5,\n 38.3\n ],\n [\n -122,\n 39\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-05-20","publicationStatus":"PW","scienceBaseUri":"59770753e4b0ec1a48889fa4","contributors":{"authors":[{"text":"Schwartz, David P. 0000-0001-5193-9200 dschwartz@usgs.gov","orcid":"https://orcid.org/0000-0001-5193-9200","contributorId":1940,"corporation":false,"usgs":true,"family":"Schwartz","given":"David","email":"dschwartz@usgs.gov","middleInitial":"P.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":706233,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lienkaemper, James J. 0000-0002-7578-7042 jlienk@usgs.gov","orcid":"https://orcid.org/0000-0002-7578-7042","contributorId":1941,"corporation":false,"usgs":true,"family":"Lienkaemper","given":"James","email":"jlienk@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":706234,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hecker, Suzanne 0000-0002-5054-372X shecker@usgs.gov","orcid":"https://orcid.org/0000-0002-5054-372X","contributorId":3553,"corporation":false,"usgs":true,"family":"Hecker","given":"Suzanne","email":"shecker@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":706235,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelson, Keith I.","contributorId":192585,"corporation":false,"usgs":false,"family":"Kelson","given":"Keith","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":706236,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fumal, Thomas E.","contributorId":195091,"corporation":false,"usgs":false,"family":"Fumal","given":"Thomas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":706237,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baldwin, John N.","contributorId":195092,"corporation":false,"usgs":false,"family":"Baldwin","given":"John","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":706238,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Seitz, Gordon G.","contributorId":139062,"corporation":false,"usgs":false,"family":"Seitz","given":"Gordon","email":"","middleInitial":"G.","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":706239,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Niemi, Tina","contributorId":195093,"corporation":false,"usgs":false,"family":"Niemi","given":"Tina","email":"","affiliations":[],"preferred":false,"id":706240,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70189901,"text":"70189901 - 2014 - Variability common to global sea surface temperatures and runoff in the conterminous United States","interactions":[],"lastModifiedDate":"2017-08-04T10:26:20","indexId":"70189901","displayToPublicDate":"2014-06-18T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2344,"text":"Journal of Hydrometeorology","active":true,"publicationSubtype":{"id":10}},"title":"Variability common to global sea surface temperatures and runoff in the conterminous United States","docAbstract":"Singular value decomposition (SVD) is used to identify the variability common to global sea surface temperatures (SSTs) and water-balance-modeled water-year (WY) runoff in the conterminous United States (CONUS) for the 1900–2012 period. Two modes were identified from the SVD analysis; the two modes explain 25% of the variability in WY runoff and 33% of the variability in WY SSTs. The first SVD mode reflects the variability of the El Niño–Southern Oscillation (ENSO) in the SST data and the hydroclimatic effects of ENSO on WY runoff in the CONUS. The second SVD mode is related to variability of the Atlantic multidecadal oscillation (AMO). An interesting aspect of these results is that both ENSO and AMO appear to have nearly equivalent effects on runoff variability in the CONUS. However, the relatively small amount of variance explained by the SVD analysis indicates that there is little covariation between runoff and SSTs, suggesting that SSTs may not be a viable predictor of runoff variability for most of the conterminous United States.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JHM-D-13-097.1","usgsCitation":"McCabe, G., and Wolock, D.M., 2014, Variability common to global sea surface temperatures and runoff in the conterminous United States: Journal of Hydrometeorology, v. 15, p. 714-725, https://doi.org/10.1175/JHM-D-13-097.1.","productDescription":"12 p.","startPage":"714","endPage":"725","ipdsId":"IP-051813","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":472934,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jhm-d-13-097.1","text":"Publisher Index Page"},{"id":344586,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":706689,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70112701,"text":"sir20145067 - 2014 - Estimates of inorganic nitrogen wet deposition from precipitation for the conterminous United States, 1955-84","interactions":[],"lastModifiedDate":"2016-06-29T13:39:51","indexId":"sir20145067","displayToPublicDate":"2014-06-17T13:03:00","publicationYear":"2014","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":"2014-5067","title":"Estimates of inorganic nitrogen wet deposition from precipitation for the conterminous United States, 1955-84","docAbstract":"The U.S. Geological Survey’s National Water-Quality Assessment program requires nutrient input information for analysis of national and regional assessment of water quality. Historical data are needed to lengthen the data record for assessment of trends in water quality. This report provides estimates of inorganic nitrogen deposition from precipitation for the conterminous United States for 1955–56, 1961–65, and 1981–84. The estimates were derived from ammonium, nitrate, and inorganic nitrogen concentrations in atmospheric wet deposition and precipitation-depth data. This report documents the sources of these data and the methods that were used to estimate the inorganic nitrogen deposition. Tabular datasets, including the analytical results, precipitation depth, and calculated site-specific precipitation-weighted concentrations, and raster datasets of nitrogen from wet deposition are provided as appendixes in this report.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145067","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Gronberg, J., Ludtke, A.S., and Knifong, D.L., 2014, Estimates of inorganic nitrogen wet deposition from precipitation for the conterminous United States, 1955-84: U.S. Geological Survey Scientific Investigations Report 2014-5067, Report: viii, 18 p.; Appendixes 1-4, https://doi.org/10.3133/sir20145067.","productDescription":"Report: viii, 18 p.; Appendixes 1-4","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1955-01-01","temporalEnd":"1984-12-31","ipdsId":"IP-051313","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":288691,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145067.jpg"},{"id":288688,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5067/downloads/sir2014-5067_Appendix_2_Lodge_data.xlsx"},{"id":288689,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5067/downloads/sir2014-5067_Appendix_3_noaa_data.xlsx"},{"id":288690,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5067/downloads/sir2014-5067_Appendix_4_Pearson_data.xlsx"},{"id":288686,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5067/pdf/sir2014-5067.pdf"},{"id":288687,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5067/downloads/sir2014-5067_Appendix_1_Junge_data.xlsx"},{"id":288679,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5067/"}],"country":"United States","geographicExtents":"{\n \"type\": 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,{"id":70049779,"text":"ds796 - 2014 - California Groundwater Units","interactions":[],"lastModifiedDate":"2018-06-08T14:21:10","indexId":"ds796","displayToPublicDate":"2014-06-17T12:47:00","publicationYear":"2014","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":"796","title":"California Groundwater Units","docAbstract":"The California Groundwater Units dataset classifies and delineates areas within the State of California into one of three groundwater-based polygon units: (1) those areas previously defined as alluvial groundwater basins or subbasins, (2) highland areas that are adjacent to and topographically upgradient of groundwater basins, and (3) highland areas not associated with a groundwater basin, only a hydrogeologic province. In total, 938 Groundwater Units are represented. The Groundwater Units dataset relates existing groundwater basins with their newly delineated highland areas which can be used in subsequent hydrologic studies. The methods used to delineate groundwater-basin-associated highland areas are similar to those used to delineate a contributing area (such as for a lake or water body); the difference is that highland areas are constrained to the immediately surrounding upslope (upstream) area. Upslope basins have their own delineated highland. A geoprocessing tool was created to facilitate delineation of highland areas for groundwater basins and subbasins and is available for download.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds796","usgsCitation":"Johnson, T., and Belitz, K., 2014, California Groundwater Units: U.S. Geological Survey Data Series 796, Report: iv, 34 p.; GIS; Metadata, https://doi.org/10.3133/ds796.","productDescription":"Report: iv, 34 p.; GIS; Metadata","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-037814","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":288685,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds796.jpg"},{"id":288682,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/796/pdf/ds796.pdf"},{"id":288684,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/796/downloads/ds796_metadata.txt"},{"id":288683,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/ds/796/downloads/ds796_GIS.zip"},{"id":288678,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/796/"}],"country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.507642,32.425413 ], [ -124.507642,42.067151 ], [ -113.488240,42.067151 ], [ -113.488240,32.425413 ], [ -124.507642,32.425413 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae764ee4b0abf75cf2bf14","contributors":{"authors":[{"text":"Johnson, Tyler D. 0000-0002-7334-9188","orcid":"https://orcid.org/0000-0002-7334-9188","contributorId":64366,"corporation":false,"usgs":true,"family":"Johnson","given":"Tyler D.","affiliations":[],"preferred":false,"id":486109,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":486108,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70110917,"text":"ds808 - 2014 - Summary of suspended-sediment concentration data, San Francisco Bay, California, water year 2010","interactions":[],"lastModifiedDate":"2017-10-30T11:29:30","indexId":"ds808","displayToPublicDate":"2014-06-17T12:38:00","publicationYear":"2014","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":"808","title":"Summary of suspended-sediment concentration data, San Francisco Bay, California, water year 2010","docAbstract":"Suspended-sediment concentration data were collected by the U.S. Geological Survey in San Francisco Bay during water year 2010 (October 1, 2009–September 30, 2010). Turbidity sensors and water samples were used to monitor suspended-sediment concentration at two sites in Suisun Bay, one site in San Pablo Bay, three sites in Central San Francisco Bay, and one site in South San Francisco Bay. Sensors were positioned at two depths at most sites to help define the vertical variability of suspended sediments. Water samples were collected periodically and analyzed for concentrations of suspended sediment. The results of the analyses were used to calibrate the output of the turbidity sensors so that a record of suspended-sediment concentrations could be computed. This report presents the data-collection methods used and summarizes, in graphs, the suspended-sediment concentration data collected from October 2009 through September 2010. Calibration curves and plots of the processed data for each sensor also are presented.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds808","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, San Francisco District","usgsCitation":"Buchanan, P.A., and Morgan, T., 2014, Summary of suspended-sediment concentration data, San Francisco Bay, California, water year 2010: U.S. Geological Survey Data Series 808, viii, 42 p., https://doi.org/10.3133/ds808.","productDescription":"viii, 42 p.","numberOfPages":"54","onlineOnly":"Y","temporalStart":"2009-10-01","temporalEnd":"2010-09-30","ipdsId":"IP-028604","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":288681,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds808.PNG"},{"id":288677,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/808"},{"id":288680,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/808/pdf/ds808.pdf"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay;San Pablo Bay;Suisun Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.5992,37.3385 ], [ -122.5992,38.1821 ], [ -121.7464,38.1821 ], [ -121.7464,37.3385 ], [ -122.5992,37.3385 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae784de4b0abf75cf2d048","contributors":{"authors":[{"text":"Buchanan, Paul A. 0000-0002-4796-4734 buchanan@usgs.gov","orcid":"https://orcid.org/0000-0002-4796-4734","contributorId":1018,"corporation":false,"usgs":true,"family":"Buchanan","given":"Paul","email":"buchanan@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494201,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morgan, Tara L. 0000-0001-5632-5232","orcid":"https://orcid.org/0000-0001-5632-5232","contributorId":29124,"corporation":false,"usgs":true,"family":"Morgan","given":"Tara L.","affiliations":[],"preferred":false,"id":494202,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70112699,"text":"70112699 - 2014 - Gas hydrate identified in sand-rich inferred sedimentary section using downhole logging and seismic data in Shenhu area, South China Sea","interactions":[],"lastModifiedDate":"2014-06-17T11:23:36","indexId":"70112699","displayToPublicDate":"2014-06-17T11:19:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Gas hydrate identified in sand-rich inferred sedimentary section using downhole logging and seismic data in Shenhu area, South China Sea","docAbstract":"Downhole wireline log (DWL) data was acquired from eight drill sites during China's first gas hydrate drilling expedition (GMGS-1) in 2007. Initial analyses of the acquired well log data suggested that there were no significant gas hydrate occurrences at Site SH4. However, the re-examination of the DWL data from Site SH4 indicated that there are two intervals of high resistivity, which could be indicative of gas hydrate. One interval of high resistivity at depth of 171–175 m below seafloor (mbsf) is associated with a high compressional- wave (P-wave) velocities and low gamma ray log values, which suggests the presence of gas hydrate in a potentially sand-rich (low clay content) sedimentary section. The second high resistivity interval at depth of 175–180 mbsf is associated with low P-wave velocities and low gamma values, which suggests the presence of free gas in a potentially sand-rich (low clay content) sedimentary section. Because the occurrence of free gas is much shallower than the expected from the regional depth of the bottom simulating reflector (BSR), the free gas could be from the dissociation of gas hydrate during drilling or there may be a local anomaly in the depth to the base of the gas hydrate stability zone. In order to determine whether the low P-wave velocity with high resistivity is caused by in-situ free gas or dissociated free gas from the gas hydrate, the surface seismic data were also used in this analysis. The log analysis incorporating the surface seismic data through the construction of synthetic seismograms using various models indicated the presence of free gas directly in contact with an overlying gas hydrate-bearing section. The occurrence of the anomalous base of gas hydrate stability at Site SH4 could be caused by a local heat flow conditions. This paper documents the first observation of gas hydrate in what is believed to be a sand-rich sediment in Shenhu area of the South China Sea.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine and Petroleum Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2014.01.002","usgsCitation":"Wang, X., Lee, M.W., Collett, T.S., Yang, S., Guo, Y., and Wu, S., 2014, Gas hydrate identified in sand-rich inferred sedimentary section using downhole logging and seismic data in Shenhu area, South China Sea: Marine and Petroleum Geology, v. 51, p. 298-306, https://doi.org/10.1016/j.marpetgeo.2014.01.002.","productDescription":"9 p.","startPage":"298","endPage":"306","numberOfPages":"9","ipdsId":"IP-053736","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":288675,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288674,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.marpetgeo.2014.01.002"}],"country":"China","state":"Shenhu","otherGeospatial":"South China Sea","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 108.44,17.02 ], [ 108.44,23.98 ], [ 121.08,23.98 ], [ 121.08,17.02 ], [ 108.44,17.02 ] ] ] } } ] }","volume":"51","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae76d0e4b0abf75cf2c030","contributors":{"authors":[{"text":"Wang, Xiujuan","contributorId":87071,"corporation":false,"usgs":true,"family":"Wang","given":"Xiujuan","affiliations":[],"preferred":false,"id":494850,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lee, Myung W. mlee@usgs.gov","contributorId":779,"corporation":false,"usgs":true,"family":"Lee","given":"Myung","email":"mlee@usgs.gov","middleInitial":"W.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":494845,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":494846,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yang, Shengxiong","contributorId":74306,"corporation":false,"usgs":true,"family":"Yang","given":"Shengxiong","affiliations":[],"preferred":false,"id":494849,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Guo, Yiqun","contributorId":68659,"corporation":false,"usgs":false,"family":"Guo","given":"Yiqun","affiliations":[{"id":34423,"text":"Guangzhou Marine Geological Survey, Guangzhou, China","active":true,"usgs":false}],"preferred":false,"id":494848,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wu, Shiguo","contributorId":11126,"corporation":false,"usgs":true,"family":"Wu","given":"Shiguo","affiliations":[],"preferred":false,"id":494847,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70188618,"text":"70188618 - 2014 - Frequency-dependent seismic attenuation in the eastern United States as observed from the 2011 central Virginia earthquake and aftershock sequence","interactions":[],"lastModifiedDate":"2017-06-19T09:57:49","indexId":"70188618","displayToPublicDate":"2014-06-17T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Frequency-dependent seismic attenuation in the eastern United States as observed from the 2011 central Virginia earthquake and aftershock sequence","docAbstract":"Ground shaking due to earthquakes in the eastern United States (EUS) is felt at significantly greater distances than in the western United States (WUS) and for some earthquakes it has been shown to display a strong preferential direction. Shaking intensity variation can be due to propagation path effects, source directivity, and/or site amplification. In this paper, we use S and Lg waves recorded from the 2011 central Virginia earthquake and aftershock sequence, in the Central Virginia Seismic Zone, to quantify attenuation as frequency‐dependent Q(f). In support of observations based on shaking intensity, we observe high Q values in the EUS relative to previous studies in the WUS with especially efficient propagation along the structural trend of the Appalachian mountains. Our analysis of Q(f) quantifies the path effects of the northeast‐trending felt distribution previously inferred from the U.S. Geological Survey (USGS) “Did You Feel It” data, historic intensity data, and the asymmetrical distribution of rockfalls and landslides.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120130045","usgsCitation":"McNamara, D.E., Gee, L., Benz, H.M., and Chapman, M., 2014, Frequency-dependent seismic attenuation in the eastern United States as observed from the 2011 central Virginia earthquake and aftershock sequence: Bulletin of the Seismological Society of America, v. 104, no. 1, p. 55-72, https://doi.org/10.1785/0120130045.","productDescription":"18 p.","startPage":"55","endPage":"72","ipdsId":"IP-045883","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":342629,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89,\n 30\n ],\n [\n -70,\n 30\n ],\n [\n -70,\n 44\n ],\n [\n -89,\n 44\n ],\n [\n -89,\n 30\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"104","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-01-14","publicationStatus":"PW","scienceBaseUri":"5948e2a7e4b062508e354c76","contributors":{"authors":[{"text":"McNamara, Daniel E. 0000-0001-6860-0350 mcnamara@usgs.gov","orcid":"https://orcid.org/0000-0001-6860-0350","contributorId":402,"corporation":false,"usgs":true,"family":"McNamara","given":"Daniel","email":"mcnamara@usgs.gov","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":698625,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gee, Lind 0000-0003-2883-9847 lgee@usgs.gov","orcid":"https://orcid.org/0000-0003-2883-9847","contributorId":193064,"corporation":false,"usgs":true,"family":"Gee","given":"Lind","email":"lgee@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":698626,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Benz, Harley M. 0000-0002-6860-2134 benz@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-2134","contributorId":794,"corporation":false,"usgs":true,"family":"Benz","given":"Harley","email":"benz@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":698627,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chapman, Martin","contributorId":45622,"corporation":false,"usgs":true,"family":"Chapman","given":"Martin","affiliations":[],"preferred":false,"id":698628,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70156379,"text":"70156379 - 2014 - An integrated approach to the Taxonomic identification of prehistoric shell ornaments","interactions":[],"lastModifiedDate":"2015-08-20T13:27:22","indexId":"70156379","displayToPublicDate":"2014-06-17T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"An integrated approach to the Taxonomic identification of prehistoric shell ornaments","docAbstract":"Shell beads appear to have been one of the earliest examples of personal adornments. Marine shells identified far from the shore evidence long-distance transport and imply networks of exchange and negotiation. However, worked beads lose taxonomic clues to identification, and this may be compounded by taphonomic alteration. Consequently, the significance of this key early artefact may be underestimated. We report the use of bulk amino acid composition of the stable intra-crystalline proteins preserved in shell biominerals and the application of pattern recognition methods to a large dataset (777 samples) to demonstrate that taxonomic identification can be achieved at genus level. Amino acid analyses are fast (<2 hours per sample) and micro-destructive (sample size <2 mg). Their integration with non-destructive techniques provides a valuable and affordable tool, which can be used by archaeologists and museum curators to gain insight into early exploitation of natural resources by humans. Here we combine amino acid analyses, macro- and microstructural observations (by light microscopy and scanning electron microscopy) and Raman spectroscopy to try to identify the raw material used for beads discovered at the Early Bronze Age site of Great Cornard (UK). Our results show that at least two shell taxa were used and we hypothesise that these were sourced locally.
","language":"English","publisher":"Plos One","doi":"10.1371/journal.pone.0099839","usgsCitation":"Demarchi, B., O’Connor, S., Ponzoni, A.D., Ponzoni, R.D., Sheridan, A., Penkman, K., Hancock, Y., and Wilson, J., 2014, An integrated approach to the Taxonomic identification of prehistoric shell ornaments: PLoS ONE, v. 9, no. 6, 12 p., https://doi.org/10.1371/journal.pone.0099839.","productDescription":"12 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":488046,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0099839","text":"Publisher Index Page"},{"id":307033,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"6","noUsgsAuthors":false,"publicationDate":"2014-06-17","publicationStatus":"PW","scienceBaseUri":"55d6fa2fe4b0518e3546bc1b","contributors":{"authors":[{"text":"Demarchi, Beatrice","contributorId":146780,"corporation":false,"usgs":false,"family":"Demarchi","given":"Beatrice","email":"","affiliations":[],"preferred":false,"id":568944,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Connor, Sonia","contributorId":146781,"corporation":false,"usgs":false,"family":"O’Connor","given":"Sonia","email":"","affiliations":[],"preferred":false,"id":568945,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ponzoni, Andre de Lima","contributorId":146782,"corporation":false,"usgs":false,"family":"Ponzoni","given":"Andre","email":"","middleInitial":"de Lima","affiliations":[],"preferred":false,"id":568946,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ponzoni, Raquel de Almeida Roch","contributorId":146783,"corporation":false,"usgs":false,"family":"Ponzoni","given":"Raquel","email":"","middleInitial":"de Almeida Roch","affiliations":[],"preferred":false,"id":568947,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sheridan, Alison","contributorId":146784,"corporation":false,"usgs":false,"family":"Sheridan","given":"Alison","email":"","affiliations":[],"preferred":false,"id":568948,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Penkman, Kirsty","contributorId":146785,"corporation":false,"usgs":false,"family":"Penkman","given":"Kirsty","email":"","affiliations":[],"preferred":false,"id":568949,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hancock, Y.","contributorId":146786,"corporation":false,"usgs":false,"family":"Hancock","given":"Y.","email":"","affiliations":[],"preferred":false,"id":568950,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wilson, Julie","contributorId":146787,"corporation":false,"usgs":false,"family":"Wilson","given":"Julie","email":"","affiliations":[],"preferred":false,"id":568951,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70111257,"text":"70111257 - 2014 - Relationship of weed shiner and young-of-year bluegill and largemouth bass abundance to submersed aquatic vegetation in Navigation Pools 4, 8, and 13 of the Upper Mississippi River, 1998-2012","interactions":[],"lastModifiedDate":"2014-06-17T09:44:18","indexId":"70111257","displayToPublicDate":"2014-06-16T15:31:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":44,"text":"Long Term Resource Monitoring Program Technical Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"2014-T001","title":"Relationship of weed shiner and young-of-year bluegill and largemouth bass abundance to submersed aquatic vegetation in Navigation Pools 4, 8, and 13 of the Upper Mississippi River, 1998-2012","docAbstract":"Aquatic vegetation provides food resources and shelter for many species of fish. This study found a significant relationship between increases in submersed aquatic vegetation (SAV) in four study reaches of the Upper Mississippi River (UMR) and increases in catch-per-unit-effort (CPUE) of weed shiners (Notropis texanus) and age-0 bluegills (Lepomis macrochirus) and largemouth bass (Micropterus salmoides) when all of the study reaches were treated collectively using Long Term Resource Monitoring Program (LTRMP) vegetation and fish data for 1998–2012. The selected fishes were more abundant in study reaches with higher SAV frequencies (Pool 8 and Lower Pool 4) and less abundant in reaches with lower SAV frequencies (Pool 13 and Upper Pool 4). When each study reach was examined independently, the relationship between SAV frequency and CPUE of the three species was not significant in most cases, the primary exception being weed shiners in Lower Pool 4. Results of this study indicate that the prevalence of SAV does affect relative abundance of these vegetation-associated fish species. However, the poor annual relationship between SAV frequency and age-0 relative abundance in individual study reaches indicates that several other factors also govern age-0 abundance. The data indicate that there may be a SAV frequency threshold in backwaters above which there is not a strong relationship with abundance of these fish species. This is indicated by the high annual CPUE variability of the three selected fishes in backwaters of Pool 8 and Lower Pool 4 when SAV exceeded certain frequencies.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","collaboration":"A product of the Long Term Resource Monitoring Program, an element of the U.S. Army Corps of Engineers’ Upper Mississippi River Restoration-Environmental Management Program","usgsCitation":"DeLain, S.A., and Popp, W.A., 2014, Relationship of weed shiner and young-of-year bluegill and largemouth bass abundance to submersed aquatic vegetation in Navigation Pools 4, 8, and 13 of the Upper Mississippi River, 1998-2012: Long Term Resource Monitoring Program Technical Report 2014-T001, v. 2014-T001, vii, 29 p.","productDescription":"vii, 29 p.","numberOfPages":"42","onlineOnly":"Y","temporalStart":"1998-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-007949","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":288669,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/mis/ltrmp2014-t001/pdf/ltrmp2014-t001.pdf"},{"id":288670,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/70111257.jpg"},{"id":288029,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/mis/ltrmp2014-t001/"}],"country":"United States","otherGeospatial":"Upper Mississippi River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -97.24,36.0 ], [ -97.24,49.38 ], [ -87.5,49.38 ], [ -87.5,36.0 ], [ -97.24,36.0 ] ] ] } } ] }","volume":"2014-T001","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae780ae4b0abf75cf2c899","contributors":{"authors":[{"text":"DeLain, Steven A.","contributorId":76032,"corporation":false,"usgs":true,"family":"DeLain","given":"Steven","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":494314,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Popp, Walter A.","contributorId":75858,"corporation":false,"usgs":true,"family":"Popp","given":"Walter","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":494313,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70112450,"text":"70112450 - 2014 - Modeling regeneration responses of big sagebrush (Artemisia tridentata) to abiotic conditions","interactions":[],"lastModifiedDate":"2014-06-16T14:03:08","indexId":"70112450","displayToPublicDate":"2014-06-16T12:06:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Modeling regeneration responses of big sagebrush (Artemisia tridentata) to abiotic conditions","docAbstract":"Ecosystems dominated by big sagebrush, Artemisia tridentata Nuttall (Asteraceae), which are the most widespread ecosystems in semiarid western North America, have been affected by land use practices and invasive species. Loss of big sagebrush and the decline of associated species, such as greater sage-grouse, are a concern to land managers and conservationists. However, big sagebrush regeneration remains difficult to achieve by restoration and reclamation efforts and there is no regeneration simulation model available. We present here the first process-based, daily time-step, simulation model to predict yearly big sagebrush regeneration including relevant germination and seedling responses to abiotic factors. We estimated values, uncertainty, and importance of 27 model parameters using a total of 1435 site-years of observation. Our model explained 74% of variability of number of years with successful regeneration at 46 sites. It also achieved 60% overall accuracy predicting yearly regeneration success/failure. Our results identify specific future research needed to improve our understanding of big sagebrush regeneration, including data at the subspecies level and improved parameter estimates for start of seed dispersal, modified wet thermal-time model of germination, and soil water potential influences. We found that relationships between big sagebrush regeneration and climate conditions were site specific, varying across the distribution of big sagebrush. This indicates that statistical models based on climate are unsuitable for understanding range-wide regeneration patterns or for assessing the potential consequences of changing climate on sagebrush regeneration and underscores the value of this process-based model. We used our model to predict potential regeneration across the range of sagebrush ecosystems in the western United States, which confirmed that seedling survival is a limiting factor, whereas germination is not. Our results also suggested that modeled regeneration suitability is necessary but not sufficient to explain sagebrush presence. We conclude that future assessment of big sagebrush responses to climate change will need to account for responses of regenerative stages using a process-based understanding, such as provided by our model.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Modelling","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2014.04.021","usgsCitation":"Schlaepfer, D., Lauenroth, W.K., and Bradford, J.B., 2014, Modeling regeneration responses of big sagebrush (Artemisia tridentata) to abiotic conditions: Ecological Modelling, v. 286, p. 66-77, https://doi.org/10.1016/j.ecolmodel.2014.04.021.","productDescription":"12 p.","startPage":"66","endPage":"77","numberOfPages":"12","ipdsId":"IP-049397","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":288625,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288601,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolmodel.2014.04.021"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.79,29.95 ], [ -124.79,49.0 ], [ -99.93,49.0 ], [ -99.93,29.95 ], [ -124.79,29.95 ] ] ] } } ] }","volume":"286","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae777de4b0abf75cf2c14d","contributors":{"authors":[{"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":494742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lauenroth, William K.","contributorId":80982,"corporation":false,"usgs":false,"family":"Lauenroth","given":"William","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":494741,"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":494740,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}