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Two identical Radar Stage Sensors from Forest Technology Systems, were evaluated to determine if they are suitable for U.S. Geological Survey (USGS) hydrologic data collection. The sensors were evaluated in laboratory conditions to evaluate the distance accuracy of the sensor over the manufacturer’s specified operating temperatures and distance to water ranges. Laboratory results were compared to the manufacturer’s accuracy specification of ±0.007 foot (ft) and the USGS Office of Surface Water (OSW) policy requirement that water level sensors have a measurement uncertainty of no more than 0.01 ft or 0.20 percent of the indicated reading. In the temperature chamber test, both sensors were within the manufacturer’s...
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An initial reconnaissance survey in March 2016 and a subsequent survey in July 2016 was conducted to identify possible groundwater discharge points along the stream reach using a forward-looking infrared (FLIR) camera in seasonal extremes. The high-resolution thermal imaging camera captures the emitted infrared radiation of the objects in view. Recent studies using similar ground-based thermal infrared imaging techniques have been successful in qualitatively locating groundwater discharge along discrete features, such as fractures and faults, as well as diffuse seepage along stream banks (Deitchman and Loheide, 2009; Pandey and others, 2013). Sites of interest were those where temperature differences were observed...
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Observed water temperatures from 1980-2019 were compiled for 2,332 lakes in the US. These data were used as training, test, and error-estimation data for process-guided deep learning models and the evaluation of process-based models. The data are formatted as a single csv (comma separated values) file with attributes corresponding to the unique combination of lake identifier, time, and depth. Data came from a variety of sources, including the Water Quality Portal, the North Temperate Lakes Long-Term Ecological Research Project, and digitized temperature records from the MN Department of Natural Resources. This dataset is part of a larger data release of lake temperature model inputs and outputs for these same lakes...
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A vented conductivity, temperature and depth sensor (CTD, InSitu Aqua Troll) was installed at site NR1 (N 47° 04’ 16.1”/W 122° 42’ 15.5”) and continuously measured water temperature, water depth, specific conductance, and salinity at 15-minute intervals from February 11, 2016 to July 18, 2016 (159 days). The sensor was replaced with a vented water-level logger (InSitu Level Troll) on July 19, 2016 and deployed until March 19, 2018 (608 days). The site is tidally influenced and located approximately 4.1 km upstream from the mouth of the Nisqually River and within the tidal prism. The elevation (NAVD88) of the top of the deployment pipe was surveyed by RTN-GPS. Tape-down measurements from the top of the pipe to the...
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Using predicted lake temperatures from uncalibrated, process-based models (PB0) and process-guided deep learning models (PGDL), this dataset summarized a collection of thermal metrics to characterize lake temperature impacts on fish habitat for 881 lakes. Included in the metrics are daily thermal optical habitat areas and a set of over 172 annual thermal metrics.
This dataset provides shapefile outlines of the 7,150 lakes that had temperature modeled as part of this study. The format is a shapefile for all lakes combined (.shp, .shx, .dbf, and .prj files). A csv file of lake metadata is also included. This dataset is part of a larger data release of lake temperature model inputs and outputs for 7,150 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9CA6XP8).
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The temperature and surface geophysical data contained in this release have primarily been collected to support groundwater/surface water methods development, and to characterize the hydrogeological controls on native brook trout habitat. All data have been collected since 2010 along the Quashnet River corridor located on Cape Cod, MA, USA. Cape Cod is a peninsula in southeastern coastal Massachusetts, USA, composed primarily of highly permeable unconsolidated glacial moraine and outwash deposits. The largest of the Cape Cod sole-source aquifers occupies a western (landward) section of the peninsula, and is incised by several linear valleys that drain groundwater south to the Atlantic Ocean via baseflow-dominated...
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Physical and chemical changes affect the biota within urban streams at varying scales ranging from individual organisms to populations and communities creating complex interactions that present challenges for characterizing and monitoring the impact on species utilizing these freshwater habitats. Salmonids, specifically cutthroat trout (Oncorhynchus clarkii) and coho salmon (Oncorhynchus kisutch), extensively utilize small stream habitats influenced by a changing urban landscape. This study used a comprehensive fish health assessment concurrent with the U.S. Geological Survey’s Pacific Northwest Stream Quality Assessment in 2015 to quantifiy impacts from disease in juvenile coho and cutthroat salmon, impacts to...
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This metadata record describes monthly input and output data covering the period 1900-2015 for a water-balance model described in McCabe and Wolock (2011). The input datasets are precipitation (PPT) and air temperature (TAV) from the PRISM group at Oregon State University. The model outputs include estimated potential evapotranspiration (PET), actual evapotranspiration (AET), runoff (RUN) (streamflow per unit area), soil moisture storage (STO), and snowfall (SNO). The datasets are arranged in tables of monthly total or average values measured in millimeters or degrees C and then multiplied by 100. The data are indexed by the identifier PRISMID, which refers to an ASCII raster of cells in an associated file named...
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Water velocities and water-quality constituents were measured along planned survey lines, which were generally perpendicular to the shoreline and spaced 100 meters apart, over an approximately 2.3-mile section of nearshore Lake Erie on June 10-12, 2019 (survey 1), and August 19-21, 2019 (survey 2), using a 1200 kHz acoustic Doppler current profiler (ADCP), a YSI 6920 V2 multiparameter sonde, and a YSI EcoMapper autonomous underwater vehicle (AUV). Water-quality data collected in this area included near-surface and three-dimensional measurements of water temperature, specific conductance, pH, dissolved oxygen, turbidity, chlorophyll, and phycocyanin (blue-green algae). The data were geo-referenced with an integrated...
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Daily lake surface temperatures estimates for 185,549 lakes across the contiguous United States from 1980 to 2020 generated using an entity-aware long short-term memory deep learning model. In-situ measurements used for model training and evaluation are from 12,227 lakes and are included as well as daily meteorological conditions and lake properties. Median per-lake estimated error found through cross validation on lakes with in-situ surface temperature observations was 1.24 °C. The generated dataset will be beneficial for a wide range of applications including estimations of thermal habitats and the impacts of climate change on inland lakes.
Categories: Data; Tags: AL, AR, AZ, Alabama, Aquatic Biology, All tags...
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This data release contains information to support water quality modeling in the Delaware River Basin (DRB). These data support both process-based and machine learning approaches to water quality modeling, including the prediction of stream temperature. This section contains observations related to the amount and quality of water in the Delaware River Basin. Data from a subset of reservoirs in the basin include observed daily depth-resolved water temperature, water levels, diversions, and releases. Data from streams in the basin include daily flow and temperature observations. Observations were compiled from a variety of sources, including the National Water Inventory System, Water Quality Portal, EcoSHEDS stream...
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Observed water temperatures from 1980-2018 were compiled for 877 lakes in Minnesota (USA). There were four lakes included in this data release that did not have temperature observations available at the time of compilation or these data existed elsewhere and were unknown to the compilation team. These data were used as training, test, and error-estimation data for process-guided deep learning models and the evaluation of process-based models. The data are formatted as a single csv (comma separated values) file with attributes corresponding to the unique combination of lake identifier, time, and depth. Data came from a variety of sources, including the Water Quality Portal, the North Temperate Lakes Long-Term Ecological...
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A vented conductivity, temperature and depth sensor (CTD, InSitu Aqua Troll) was installed at site NR3 (N 47° 05’ 12”/W 122° 42’ 22”) and continuously measured water level, water temperature, specific conductance, and salinity at 15-minute intervals from February 12, 2016 to August 7, 2016 (177 days) and from October 7, 2016 to February 8, 2017 (124 days). This site is tidally influenced and located approximately 2.2 km upstream from the mouth of the Nisqually River. Elevation (NAVD88) of the deployment pipe was surveyed by RTN-GPS. Elevation of pipe plus distance to sensor is included in the offset. The offset needed to convert water depth to NAVD88 water surface elevation is -0.31 meters. . Water depth of the...
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Common offset ground penetrating radar (GPR) data were collected to image near surface streambed structure. These data are to be used in conjunction with fiber-optic distributed temperature sensing (FO-DTS) and electromagnetic imaging (EMI) data. The combined dataset represents point in time mapping of preferential groundwater discharge points (FO-DTS) and the bed structure that controls where these points are located (GPR, EMI).
This dataset summarized a collection of annual thermal metrics to characterize lake temperature impacts on fish habitat for 7,150 lakes from uncalibrated models (PB0) and 449 from calibrated models (PBALL). The dataset includes over 172 annual thermal metrics.
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This dataset provides model specifications used to estimate water temperature from a process-based model (Hipsey et al. 2019). The format is a single JSON file indexed for each lake based on the "site_id". This dataset is part of a larger data release of lake temperature model inputs and outputs for 68 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9AQPIVD).
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This dataset includes model inputs that describe local weather conditions for Sparkling Lake, WI. Weather data comes from two sources: locally measured (2009-2017) and gridded estimates (all other time periods). There are two comma-delimited files, one for weather data (one row per model timestep) and one for ice-flags, which are used by the process-guided deep learning model to determine whether to apply the energy conservation constraint (the constraint is not applied when the lake is presumed to be ice-covered). The ice-cover flag is a modeled output and therefore not a true measurement (see "Predictions" and "pb0" model type for the source of this prediction). This dataset is part of a larger data release of...
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Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. states of Minnesota and Wisconsin. Process-Based (PB) models were configured and calibrated with training data to reduce root-mean squared error. Uncalibrated models used default configurations (PB0; see Winslow et al. 2016 for details) and no parameters were adjusted according to model fit with observations. Deep Learning (DL) models were Long Short-Term Memory artificial recurrent neural network models which used training data to adjust model structure and weights for temperature predictions (Jia et al. 2019). Process-Guided Deep Learning (PGDL) models were DL models with an added...
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This dataset includes model inputs that describe weather conditions for the 68 lakes included in this study. Weather data comes from gridded estimates (Mitchell et al. 2004). There are two comma-separated files, one for weather data (one row per model timestep) and one for ice-flags, which are used by the process-guided deep learning model to determine whether to apply the energy conservation constraint (the constraint is not applied when the lake is presumed to be ice-covered). The ice-cover flag is a modeled output and therefore not a true measurement (see "Predictions" and "pb0" model type for the source of this prediction). This dataset is part of a larger data release of lake temperature model inputs and outputs...


map background search result map search result map Water Balance Model Inputs and Outputs for the Conterminous United States, 1900-2015 FTS RSS Temperature Test 1, John C. Stennis Space Center, Nov 2015 Evaluating Coho Salmon in Streams Across an Urbanization Gradient—Part 1, Growth Potential Based on Environmental Factors and Bioenergetics Water Data for Nisqually River at Site NR1 Water Data for Nisqually River at Site NR3 Temperature and geophysical data collected along the Quashnet River, Mashpee/Falmouth MA (ver. 2.0, March 2020) Thermal Imagery along Ellerbe Creek in Durham, North Carolina Ground penetrating radar (GPR) data collected along the Santuit River, Mashpee, MA. Process-guided deep learning water temperature predictions: 2 Model configurations (lake metadata and parameter values) Process-guided deep learning water temperature predictions: 5c All lakes historical prediction data Process-guided deep learning water temperature predictions: 3c All lakes historical inputs Process-guided deep learning water temperature predictions: 3b Sparkling Lake inputs Process-based water temperature predictions in the Midwest US: 1 Spatial data (GIS polygons for 7,150 lakes) Process-based water temperature predictions in the Midwest US: 6 Habitat metrics Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 2 Water temperature observations Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 7 thermal and optical habitat estimates Predicting Water Temperature Dynamics of Unmonitored Lakes with Meta Transfer Learning: 2 Water temperature observations Velocity surveys and three-dimensional point measurements of basic water-quality constituents in nearshore Lake Erie in the vicinity of Villa Angela Beach and Euclid Creek, Cleveland, Ohio, June 10–12, 2019, and August 19–21, 2019 Daily surface temperature predictions for 185,549 U.S. lakes with associated observations and meteorological conditions (1980-2020) Data to support water quality modeling efforts in the Delaware River Basin: 2) River and Reservoir Observations Process-guided deep learning water temperature predictions: 3b Sparkling Lake inputs Water Data for Nisqually River at Site NR3 Ground penetrating radar (GPR) data collected along the Santuit River, Mashpee, MA. Velocity surveys and three-dimensional point measurements of basic water-quality constituents in nearshore Lake Erie in the vicinity of Villa Angela Beach and Euclid Creek, Cleveland, Ohio, June 10–12, 2019, and August 19–21, 2019 Temperature and geophysical data collected along the Quashnet River, Mashpee/Falmouth MA (ver. 2.0, March 2020) Thermal Imagery along Ellerbe Creek in Durham, North Carolina Data to support water quality modeling efforts in the Delaware River Basin: 2) River and Reservoir Observations Evaluating Coho Salmon in Streams Across an Urbanization Gradient—Part 1, Growth Potential Based on Environmental Factors and Bioenergetics Process-guided deep learning water temperature predictions: 2 Model configurations (lake metadata and parameter values) Process-guided deep learning water temperature predictions: 5c All lakes historical prediction data Process-guided deep learning water temperature predictions: 3c All lakes historical inputs Process-based water temperature predictions in the Midwest US: 6 Habitat metrics Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 7 thermal and optical habitat estimates Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 2 Water temperature observations Predicting Water Temperature Dynamics of Unmonitored Lakes with Meta Transfer Learning: 2 Water temperature observations Process-based water temperature predictions in the Midwest US: 1 Spatial data (GIS polygons for 7,150 lakes) Daily surface temperature predictions for 185,549 U.S. lakes with associated observations and meteorological conditions (1980-2020) Water Balance Model Inputs and Outputs for the Conterminous United States, 1900-2015