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396 results for “surface water”
Dissolved Inorgainic Carbon concentration and Total Alkalinity from surface water samples collected in the GCE LTER domain near Sapelo Island, Georgia between May 2014 and December 2022.
Surface water samples were collected from GCE LTER sampling stations between May 2014 and December 2022. Monthly samples were collected from GCE 6 (high and low tide) and GCE 7 (high tide). Quarterly samples were collected from the remaining GCE sites, 4 sites along the Duplin River, and AL-02 ( the Altamaha River oceanic end-member station). These samples were analyzed for dissolved inorganic carbon (DIC) and total alkalinity (TA).
Composition and biodegradability of dissolved organic matter in supra-permafrost groundwater and surface waters near Simpson Lagoon, Alaska
Supra-permafrost groundwater (SPGW) is an important source of terrestrial dissolved organic matter (DOM) to the Arctic Ocean, yet few studies have investigated the quality or characteristics of this DOM. We sampled fresh SPGW, run-off, and rivers near Simpson Lagoon, Alaska during spring ice break-up (mid-June), summer open water (late July), and fall freeze-up (late September - early October). We measured dissolved organic carbon (DOC) concentrations in these samples and analyzed the composition of DOM using high-resolution mass spectrometry (Fourier transform ion cyclotron resonance mass spectrometry; FT-ICR MS). To measure biodegradable dissolved organic carbon (BDOC), we conducted an aerobic incubation experiment following the methods suggested by Vonk et al. (2015). Briefly, water samples were incubated at 20C for 28 days to measure DOC loss due to remineralization by in-situ microbial communities.
Total dissolved nitrogen (TDN), dissolved organic carbon (DOC), radiocarbon (14C-DOC), and stable carbon (13C-DOC) of surface waters from the Canning River watershed, 2019 and 2021
Sites along the Canning River mainstem and contributing streams near the Kavik River Camp, Alaska, were visited to track changes in stream and river total dissolved nitrogen (TDN) concentration, dissolved organic carbon (DOC) concentration, and the stable carbon (13C) and radiocarbon (14C) isotopic composition of DOC across transitions between the Brooks Range, Brooks foothills, and Arctic Coastal Plain. The dataset also includes water samples collected from lakes, springs, groundwater, and streams and rivers outside the Canning River watershed. Water samples were collected in late April and early August 2019 and in late July and early August 2021. Data include measurements of individual samples for TDN (milligrams nitrogen per liter), DOC (milligrams carbon per liter), carbon-13 of DOC (reported as delta-13C, per mil), carbon-14 of DOC (reported as fraction modern), and analytical error in the fraction modern values. Additional water chemistry data for these samples can be found in Koch et al. (2024). References: Koch, J. C., Connolly, C. T., Repasch, M., Best, H. R., Couvillion, C. S., Hunt, A. (2024). [Dataset] Hydrochemistry and age date tracers from springs, streams, and rivers in the Arctic National Wildlife Refuge, 2019-2022, U.S. Geological Survey data release, https://doi.org/10.5066/P95CXJIT.
WSC 2007 - 2012 Yahara Watershed surface water quality policies and practices created and implemented by public agencies
This dataset was created June 2012 - August 2013 to contribute to research under the Water Sustainability and Climate project. Interventions collected are those land-based policies and practices written and implemented by public agencies. Policies were implemented in Wisconsin's Yahara Watershed the period 2007-2012. They aim to improve surface water quality through nutrient (phosphorus and nitrogen) and sediment reduction. Interventions included in the mapping must have spatially-explicit, publicly available data through personal communication or website.
WSC - Water surface elevation (WSE) and water table depth (WTD) from 14 points at the Wibu field site, 2012-2013 growing seasons
Observation wells were installed for the purpose of continuously monitoring the water table level during the 2012 and 2013 growing seasons at the Wibu field site. These data were then used to study the yield response of corn to water table depth, soil texture, and growing season weather conditions (Zipper et al., in prep). The Wibu field site is a commercial agricultural field, which grew corn in the 2012, 2013, and 2014 growing seasons. See Zipper and Loheide (2014) Ag. For. Met. for more information about the field site. The 2012 growing season was characterized by severe drought, and the water table fell below the bottom of most wells in late June/early July.
LAGOS-US LIMNO: Data module of surface water chemistry from 1975-2021 for lakes in the conterminous U.S.
The LAGOS-US LIMNO data package is one of the core data modules of LAGOS-US, an extensible research-ready platform designed to study the 479,950 lakes and reservoirs larger than or equal to 1 ha in the conterminous US (48 states plus the District of Columbia). The LIMNO module contains in situ observations of 47 parameters of lake physics, chemistry, and biology (hereafter referred to as chemistry) from lake surface samples (defined as observations taken from the epilimnion of a lake) obtained from the Water Quality Portal, the National Lakes Assessment (2007, 2012, 2017), and NEON programs. LIMNO provides 3,511,020 observations across all parameters collected between 1975 and 2021 from 20,329 lakes; the number of observations per lake ranged from 1 to 20,605 with a median of 32. The database design that supports the LAGOS-US research platform was created based on several important design features: lakes are the fundamental unit of consideration, all lakes in the spatial extent above the minimum size must be represented, and most information is connected to individual lakes. The design is modular, interoperable (the modules can be used with each other, as well as other comprehensive lake data products such as the USGS NHD), and extensible (future database modules can be developed and used in the LAGOS-US research platform by others). Users are encouraged to use the other two core data modules that are part of the LAGOS-US platform: LOCUS (location, identifiers, and physical characteristics of lakes and their watersheds) and GEO (characteristics defining geospatial and temporal ecological setting quantified at multiple spatial divisions) that are each found in their own data packages.
H2Ohio Wetland Monitoring Program Surface Water and Soil Nutrient Content from Wetlands across Ohio, USA (2021–2022).
This data package contains surface water and soil nutrient concentration datasets from wetland projects across Ohio, USA monitored by the H2Ohio Wetland Monitoring Program. Monitoring began in May 2021 and is ongoing. This data package will be updated yearly. In general, surface water samples are collected to measure concentrations of major nutrients, including inorganic nitrogen, ammonium-nitrogen, total nitrogen, dissolved reactive phosphorus, and total phosphorus. Sampling from major inflows and outflows is prioritized at flow-through wetland projects to support the calculation of nutrient filtration estimates using mass balance approaches. Surface water samples may also be collected from representative zones or hydrologic features with sufficient standing water (i.e., vernal pools, vegetated areas, interconnected smaller pond-like areas, etc.) to assess nutrient conditions and processes within the wetland system. The majority of surface water sampling (~monthly) occurs from March through December, with opportunistic sampling in January and February. Every effort is made to collect samples during hydrologic events (i.e., storms) as well as baseflow conditions. Concurrent with surface water sampling, hand-held multiparameter sensors are used to measure snapshots of physicochemical characteristics including dissolved oxygen, temperature, specific conductance, turbidity, and pH. Soil samples (0-5 cm) are collected in saturated and unsaturated zones at each identified soil "patch" determined from expert opinion, soil maps (Natural Resources Conservation Service), and/or hydrogeophysical assessment. Additionally, soil samples may be collected along major visible hydrologic or elevation gradients. Soil sampling occurs 1-3 times a year in select wetland projects.
Spatial surface water chemistry of Lake Mendota with FLAMe: 2014-2016
We mapped surface water chemistry in Lake Mendota 39 times between 2014 and 2016. We used a sensor-based and boat-mounted sensing platform to continuously measure underway water chemistry. Measurements were linked with global positioning systems (GPS) to create maps of surface water chemistry. Data have been provided in three formats (raw, hydraulic-corrected, and tau-corrected). Dataset is used for the publication, "Large spatial and temporal variability of carbon dioxide and methane in a eutrophic lake", https://doi.org/10.1029/2019JG005186
SBC LTER: Ocean: HFR-derived surface flow metrics, surface water retention times, and related factors in the Santa Barbara Channel (2012-2019)
This data package include three files: 1. daily maps of High-Frequency Radar (HFR) measured surface currents, indices of mesoscale eddy locations, and local retention times on a 2km grid; 2. monthly time series of wind stress, alongshore pressure gradient, surface current EOF principal components, vorticity, eddy area, eddy presence, and spatially averaged retention times from January 2012 to December 2019; 3. A MATLAB script for plotting the maps and timeseries. These data were processed in order to investigate the drivers of surface water retention in the Santa Barbara Channel, CA, details of which are available in the study: Brokaw, R.J., D.A. Siegel, and L. Washburn. Physical Drivers of Surface Water Retention in the Santa Barbara Channel. [In preparation for Journal of Geophysical Research: Oceans.]
Surface water quality from the Seagrass Recovery Experiment, South Bay, VA 2020-2022
To understand intra-meadow stability, the Seagrass Recovery Experiment was designed to ask 1) is recovery faster at sites with less thermal stress owing to greater exchange with cooler oceanic water at the meadow edge? 2) what is the shape of recovery? and 3) what are the recovery mechanisms? To conduct this experiment, aboveground seagrass biomass was removed from 28.3 m2 plots within the interior and along an edge of a restored seagrass meadow in South Bay, VA. Sites 1-3 correspond to the meadow interior while sites 4-6 correspond to the northern edge. Each site was comprised of a control (i.e., C) where no seagrass was disturbed and a treatment (i.e., T) where seagrass was removed (n = 12 sites total, e.g., 1C, 1T, 2C...). To further characterize differences between the meadow interior and edge, surface water quality samples were also collected and include turbidity, total suspended solids (TSS) concentration, TSS ash-free dry weight, TSS percent organic matter, pelagic chlorophyll concentration, dissolved oxygen saturation, dissolved oxygen concentration, salinity, water temperature, and specific conductivity. These discrete samples were collected monthly between June-October 2020, May-October 2021, and April-October 2022 using a 1-L Nalgene bottle and a handheld YSI Pro Plus Multiparameter meter.
Surface water and flooding dynamics data set based on seasonally continuous Landsat data (1986-2011) in a dryland river basin
<p>Animations of the data are available here: <a href="https://doi.org/10.5281/zenodo.2438110">https://doi.org/10.5281/zenodo.2438110</a></p> <p>If you are using this data set, please cite the following publication:</p> <p>Tulbure, M.G. and M. Broich (2018). Spatiotemporal patterns and effects of climate and land use on surface water extent dynamics in a dryland region with three decades of Landsat satellite data. Science of the Total Environment. https://www.sciencedirect.com/science/article/pii/S0048969718347466 </p> <p>The data represent statistically validated surface water and flooding extent dynamics derived from seasonally continous Landsat TM/ETM+ data and random forest models, and summarised to the maximum extent of surface water per season between 1986-2011 over Australia's Murray-Darling Basin. The overall accuracy was over 99% and producer's accuracy for water 87% +/- 3%. </p> <p>The method is described in the following publication: <br> Tulbure, M.G., M. Broich, S.V. Stehman, A. Kommareddy. (2016). Surface water extent dynamics from three decades of seasonally continuous Landsat time series at subcontinental scale in a semi-arid region. Remote Sensing of Environment. 178: 142-157</p> <p>URL: https://www.sciencedirect.com/science/article/pii/S0034425716300621 </p> <p>Data are provided in GeoTIFF format per season per year. File naming convention is as follows:<br> yy_inund_freq_season_SamplingMethod. For example, "99_inund_freq_winter_max" will represent inundation frequency for winter 1999 resampled using a maximum resampling method. </p> <p>Inundation frequency represents the number of times a pixel has been flagged as flooded out of the times that pixel had valid observations * 100. Valid observation exclude no data values and clouds. The valid range of inundation frequency is 0-100 [%], with 255 indicating no data values. Data type is eight bit unsigned integer (uint8). </p> <p>The data were resampled to 120m resolution to reduce file size. The resampling methods used include max (e.g. selects the max value of all non-NODATA contributing 30m pixels) and mean (median and min can be provided upon request). If you are unsure which resampling to use, you may want to start with the mean. </p>
Marcell Experimental Forest chemistry of surface water draining the S2 catchment, 1986 - ongoing
This data set is a record since 1986 of chemistry for surface water draining the S2 catchment at the Marcell Experimental Forest (MEF) in Itasca County, Minnesota. Unfiltered water is usually collected every one or two weeks as part of the long-term monitoring program of the S2 catchment. Some samples were collected more often for various other studies and are included in this data set. Samples are routinely measured for pH, specific conductivity, anions (chloride, sulfate), cations (calcium, magnesium, potassium, sodium, aluminum, iron, manganese, strontium), silicon, nutrients (ammonium, nitrate+nitrite, soluble reactive phosphorus, total nitrogen, total phosphorus), and total organic carbon. Occasionally, stable water and mercury isotopes as well as concentrations of dissolved organic carbon (DOC), bacterial respiration of dissolved organic matter, biodegradable DOC (BDOC), ferrous and ferric iron, total mercury (filtered or unfiltered), methylmercury (filtered or unfiltered), and lead were measured. Ultraviolet (UV) absorbance, a measure of water color or dissolved organic matter optical properties, was also measured for some samples. More solutes and values will be added as additional metadata are documented (pre-1986 to 1992), water samples are collected and analyzed (concentrations and isotopes), or archived water samples are analyzed for stable water isotopes. The MEF is operated and maintained by the USDA Forest Service, Northern Research Station.
National Park Service - South Florida/Caribbean Inventory & Monitoring Network - BISC1 SET Surface Water level data from in Biscayne National Park, Florida, USA (2016-2025)
Surface water level data (m) was collected in Biscayne National Park (BISC) by the South Florida/Caribbean Inventory and Monitoring Network (SFCN) as part of the Soil Elevation Table (SET) vital sign monitoring program. Water level data collected from 2016 to 2025 is included in this dataset. The water level data was collected using HOBOware Onset Water Level Data Loggers. This dataset belongs to Site 1, known as BISC-SET-1 or BISC1. This data-package is complete.
National Park Service - South Florida/Caribbean Inventory & Monitoring Network - BISC2 SET Surface Water level data from in Biscayne National Park, Florida, USA (2017-2025)
Water level data (m) was collected in Biscayne National Park (BISC) by the National Park Service - South Florida/Caribbean Inventory and Monitoring Network (SFCN) as part of the Soil Elevation Table (SET) vital sign monitoring program. Water level data collected from 2017-2025 is included in this dataset. The water level data was collected using HOBOware Onset Water Level Data Loggers. This dataset belongs to Site 2, known as BISC-SET-2 or BISC2. This data-package is complete.
National Park Service - South Florida/Caribbean Inventory & Monitoring Network - SARI SET Surface Water level data from Salt River Bay National Historical Park and Ecological Preserve, St. Croix, US Virgin Islands.
Surface water level data (m) was collected in Salt River Bay National Historic Park and Ecological Preserve (SARI) by the South Florida/Caribbean Inventory and Monitoring Network (SFCN) as part of the Soil Elevation Table (SET) vital sign monitoring program. Water level data collected from 2017 to 2024 is included in this dataset. The water level data was collected using HOBOware Onset Water Level Data Loggers. This data-package is complete.
National Park Service - South Florida/Caribbean Inventory & Monitoring Network - Mary's Point SET Surface Water level data from Virgin Islands National Park, St. John, US Virgin Islands
Surface water level data (m) was collected in Virgin Islands National Park, Mary's Point (MARY) by the South Florida/Caribbean Inventory and Monitoring Network (SFCN) as part of the Soil Elevation Table (SET) vital sign monitoring program. Water level data collected from 2017 to 2024 is included in this dataset. The water level data was collected using HOBOware Onset Water Level Data Loggers. This data-package is complete.
National Park Service - South Florida/Caribbean Inventory & Monitoring Network - Water Creek SET Surface Water level data from Virgin Islands National Park, St. John, US Virgin Islands
Surface water level data (m) was collected in Virgin Islands National Park, Water Creek (WACR) by the South Florida/Caribbean Inventory and Monitoring Network (SFCN) as part of the Soil Elevation Table (SET) vital sign monitoring program. Water level data collected from 2017 to 2024 is included in this dataset. The water level data was collected using HOBOware Onset Water Level Data Loggers. This data-package is complete.
Sulfate Concentrations and Sulfur Stable Isotope Ratios in Surface Water from the Marlborough and Waipara Winegrowing Regions, South Island of New Zealand, 2023
Agricultural sulfur (S) additions are a major anthropogenic source of S to the environment, yet our understanding of the downstream transformations and potential environmental consequences of these S inputs remains incomplete. This dataset includes surface water samples from the Marlborough and Waipara winegrowing regions of the South Island of New Zealand, where frequent applications of S fungicide are widespread. Samples were analyzed for sulfate concentration and S stable isotope ratios – the combination of which forms the S “fingerprint”. We collected surface water samples during the winter of 2023 from a variety of different locations and land use types, including vineyards, forests, pastures, and urban areas. The data table includes water sample sulfate concentrations, sulfate-S stable isotope measurements, and the S stable isotope composition of commonly used S-containing fungicides and fertilizers for comparison.
Stream metabolism estimates and surface water chemistry in Glenbrook Creek (NV) and Blackwood Creek (CA) in the Lake Tahoe Basin, 2021-2024
The goal of this project was to develop a process-based understanding of how in-stream productivity and nitrogen dynamics respond to hydroclimatic volatility. We used a combined approach of high-frequency sensor deployment and maintenance, ecosystem metabolism modeling, and routine monitoring of water chemistry and other parameters. The data we collected as part of this project demonstrate how variable ecosystem productivity is in time and space in within and among mountain streams. Although maintenance of the sensor arrays during the exceptionally wet winter of 2023 was challenging, we were able to estimate a time series of stream metabolism within the upper and lower reaches of two streams with different basin characteristics and through hydroclimatic conditions (2021 to 2024). Throughout this project we: 1. We generated four years of daily estimates of ecosystem metabolism (gross primary productivity, ecosystem respiration, and net ecosystem productivity) from upper and lower reach stations on both the east and west shores of the Lake Tahoe Basin. 2. We measured ammonium (NH4+) and nitrate (NO3-) concentrations in surface water and sediment samples from both Glenbrook and Blackwood creeks. 3. We modeled nitrogen supply and demand dynamics at each reach location. See this git code repository for project analysis: https://github.com/kellyloria/Mountain-stream-biogeochem-and-productivity.
Dissolved greenhouse gas concentrations derived from the NEON dissolved gases in surface water data product (DP1.20097.001)
This dataset contains partial pressure and molar concentration of dissolved carbon dioxide, methane, and nitrous oxide in 34 streams, rivers, and lakes calculated from headspace equilibration samples collected by the National Ecological Observatory Network (NEON). All input data were collected by NEON and is available on the NEON data portal at https://data.neonscience.org. Specifically, in situ dissolved gas concentrations were calculated from the air and headspace mixing ratios provided by the NEON Dissolved gases in surface water data product (DP1.20097.001), adjusted for sample and water temperature (DP1.20097.001, DP1.20264.001, DP1.20053.001), barometric pressure (DP1.20097.001, DP1.00004.001), and alkalinity (DP1.20093.001). The final set of inputs is found in the file, input_file, and the processing scripts are available at https://github.com/kellyaho/NEON-GHG-processing. The file, output_file, contains the raw outputs from running the input_file through the processing scripts. There are three outputs for each gas for each sample, one for each of three different pre-equilibration headspace mixing ratios (paired atmospheric samples, loess smoothing of atmospheric samples, and site-specific median). The file, GHG_final, contains the final dataset. This GHG_final uses the outputs from output_file calculated with paired atmospheric samples, and substitutes 0.01 μatm, 0.001 μM, 0.001 μatm, and 0.001 μM for any negative instances of pCH4, [CH4], pN2O, and [N2O], respectively. See methods for more detail. Please cite the NEON data inputs (listed below), in addition to this dataset, when using the data. NEON is sponsored by the National Science Foundation (NSF) and operated under cooperative agreement by Battelle. This material is based in part upon work supported by NSF through the NEON Program.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.