Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
484
datasets available to search
ShareScore release 0.7.1
Dataset results
484 results for “water quality”
HYPSTAR hyperspectral water reflectance and derived water quality products (suspended particulate matter and chlorophyll-a concentration) at the Blankaart surface water reservoir (BE)
<p><strong>Hyperspectral Water Leaving Reflectance spectra (2988)</strong> measured between 2021-02-03 and 2022-08-03 at the Blankaart Surface Water Reservoir (Belgium, 50.98857N, 2.835213E) with the <strong>HYPSTAR®</strong> (ID: HYPSTAR_12120241). Detailed description of the data collection, processing and analysis can be found in <strong>Goyens et al.- Remote Sens. 2022</strong> - 14(21)- 5607; https://doi.org/10.3390/rs14215607.</p> <ol> <li>HYPSTAR_W_BSBE_L2A_REFL_20210203_20220803_v1.csv</li> </ol> <p><strong>Chlorophyll-a (Chl-a) concentration and Suspended Particulate Matter (SPM) </strong>were derived from the above dataset of hyperspectral water reflectance and estimated according to different algorithms found in the litterature, i.e.,</p> <ol> <li>HYPSTAR_W_BSBE_CHLA_SIMIS_20210203_20220803_v1.csv<strong>:</strong> <strong>Chlorophyll-a concentration</strong> estimated from the <strong>HYPSTAR®</strong> reflectance measurements and following the algorithm suggested by Simis et al. (2005; https://doi.org/10.4319/lo.2005.50.1.0237) with a variable absorption coefficient of phytoplankton per unit of Chl-a concentration as described in Goyens et al. (2022)</li> <li>HYPSTAR_W_BSBE_CHLA_CRAT_20210203_20220803_v1.csv: <strong>Chlorophyll-a concentration</strong> estimated with the <strong>HYPSTAR®</strong> reflectance measurements and following the algorithm suggested by Ruddick et al. (2001; https://doi.org/10.1364/AO.40.003575.) with a variable absorption coefficient of phytoplankton per unit of Chl-a concentration as described in Goyens et al. (2022)</li> <li>HYPSTAR_W_BSBE_SPM_20210203_20220803_v1.csv: <strong>Suspended particulate matter </strong>estimated with the <strong>HYPSTAR®</strong> reflectance measurements and following the algorithm suggested by Nechad et al. (2010) at 700 nm</li> </ol>
Water quality data from s::can sensors in the Barcelona sewer system
<p>Within the frame of the SCOREwater project, BCASA and s::can installed water quality sensors in the sewer system in three neighbourhoods with different socio-economic characteristics (Poblenou, Sant Gervasi and Carmel) in the City Of Barcelona. To prevent vandalism, the exact location of the sensors cannot be disclosed. The sensors are monitoring physico-chemical parameters in the sewer network. These data can be used for multiple purposes, both related to predictive maintenance of the sewer network and life style analysis of inhabitants of Barcelona:</p> <ul> <li>a better operation and maintenance of the sewer network</li> <li>minimizing odor episodes and corrosion from H2S</li> <li>try to prevent blocking from sediments</li> <li>detect spills into the sewer system from a construction site or illegal discharge</li> <li>learn population habits from analyzing the waste water from the three different neighborhoods</li> <li>to learn about how the inhabitants use pharmaceuticals or other compounds (perhaps abusing of it).</li> </ul>
Water quality in a basin for drinking water in the North-West of Italy (2022-2023)
<p>Information about water quality in La Loggia basin was collected in different seasons in 2022 and 2023, both on the basin surface and at different depths.</p> <p>Samples were collected and analysed in lab, for the following parameters:</p> <ul> <li>Total chlorophyll</li> <li>Blue-green algae</li> <li>Diatoms</li> <li>Green algae</li> <li>Planktothrix</li> <li>Transparency</li> <li>Temperature</li> <li>Dissolved oxygen</li> <li>pH</li> <li>Conductivity</li> <li>Turbidity</li> <li>Bromide</li> <li>Bromate</li> <li>Chloride</li> <li>Chlorite</li> <li>Chlorate</li> <li>Fluoride</li> <li>Nitrite</li> <li>Nitrate</li> <li>Orthophosphate</li> <li>Sulfates</li> </ul> <p>Samples were collected in the same dates of Sentinel-2 passages, in order to be used for the of satellite derived water quality products.<br> The shared data are not representative of drinking water distributed to users, since a multi-step treatment is performed on raw water in order to assure water safety and law-compliant quality standards.</p> <p><br> The coordinates of the sampling points are also available in the dataset.</p>
LAGOS-NE-LOCUS v1.01: A module for LAGOS-NE, a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of U.S. Lakes: 1925-2013
This data package, LAGOS-NE-LOCUS v1.01, is 1 of 5 data packages associated with the LAGOS-NE database-- the LAke multi-scaled GeOSpatial and temporal database. Three of the data packages each contain different types of data for 51,101 lakes and reservoirs larger than 4 ha in 17 lake-rich U.S. states to support research on thousands of lakes. These three package are: (1) LAGOS-NE-LOCUS v1.01: lake location and physical characteristics for all lakes. (2) LAGOS-NEGEO v1.05: ecological context (i.e., the land use, geologic, climatic, and hydrologic setting of lakes) for all lakes. These geospatial data were created by processing national-scale and publicly-accessible datasets to quantify numerous metrics at multiple spatial resolutions. And, (3) LAGOS-NE-LIMNO v1.087.1: in-situ measurements of lake water quality from the past three decades for approximately 2,600-12,000 lakes, depending on the variable. This module was created by harmonizing 87 water quality datasets from federal, state, tribal, and non-profit agencies, university researchers, and citizen scientists. The other two data packages contain supporting data for the LAGOS-NE database: (4) LAGOS-NE-GIS v1.0: the GIS data layers for lakes, wetlands, and streams, as well as the spatial resolutions that were used to create the LAGOS-NE-GEO module. (5) LAGOS-NE-RAWDATA: the original 87 datasets of lake water quality prior to processing, the R code that converts the original data formats into LAGOS-NE data format, and the log file from this procedure to create LAGOS-NE. This latter data package supports the reproducibility of LAGOS-NE-LIMNO. The LAGOS-NE-LOCUS v1.01 module includes information on the physical location and features of all lakes > 4 ha. The information provided for this population of lakes includes: lake unique identifiers, lake area, perimeter, latitude and longitude, and the zone IDs that the lake is located within (e.g., state, county, the hydrologic unit at each level (4, 8, and 12). Citation for
Cyanobacteria abundance, cyanotoxin concentration, and water quality data for the upper San Francisco Estuary, California, USA: 2014-2019
The goal of these measurements was to quantify Microcystis abundance and microcystin concentration and associated water quality conditions during summer blooms in the upper San Francisco Estuary in California, USA. Blooms of harmful algae are a major ecological concern in the area because harmful algae produce toxins and other metabolites, which deteriorate water quality and negatively impact the aquatic ecosystem. Our research team collected biological, physical, and chemical data at 2-week to 4-week intervals during the summer and fall from 2014 through 2019. Data included surface measurements of Microcystis volume (area-based diameter) by microscopy (flowCAM digital imaging flow cytometry) and subsurface (1 m depth) measurements of Microcystis, Aphanizomenon and Dolichospermum cell abundance measured by quantitative PCR, cyanotoxin concentration (total microcystins, anatoxin a and saxitoxin) measured by protein phosphatase inhibition assay or enzyme linked immunosorbent assay, and a suite of water quality parameters (water temperature, dissolved oxygen, nutrient concentration, water transparency, specific conductance, turbidity, pH, and chlorophyll a concentration). Details for the field sampling and analytical methods are available in Lehman et al. (2017). We also performed shotgun metagenomic analyses to investigate biodiversity of cyanobacteria and other aquatic microorganisms and all the DNA sequencing data are publicity available (www.ncbi.nlm.nih. gov/; BioProject ID: PRJNA434758, Kurobe et al. 2018, Lehman et al. 2021). During the study, we experienced critically dry (2014 and 2015), below normal (2016 and 2018), and wet years (2017 and 2019), therefore data obtained in this study provided a unique opportunity to assess impacts of extreme conditions on the aquatic ecosystem (Kurobe et al. 2018, Lehman et al. 2020).
Interagency Ecological Program: Zooplankton and water quality data in the San Francisco Estuary collected by the Summer Townet and Fall Midwater Trawl monitoring programs.
The Interagency Ecological Program’s (IEP) Summer Townet Survey (STN) and Fall Midwater Trawl (FMWT) are two long-term monitoring projects conducted by the California Department of Fish and Wildlife (CDFW) to monitor fish abundance and distribution trends in the San Francisco Estuary (SFE) since 1959 and 1967, respectively. Starting in 2005, zooplankton monitoring was added and paired with fish tows to investigate food availability for young fishes. Food limitation has been a long-term issue and a focus of the Pelagic Organism Decline (POD) studies that began in 2005. By 2011, STN routinely conducted zooplankton monitoring at 40 stations, and FMWT at 32 stations in the upper SFE from Carquinez Strait to the Sacramento Deep Water Ship Channel and into the South Delta. STN samples every other week from June to August and FMWT samples once monthly from September to December. Both projects collect mesozooplankton samples using a modified Clarke-Bumpus (CB) net to target copepods and cladocerans, and FMWT also samples macrozooplankton (i.e. mysids and amphipods) using a mysid net. Flowmeters are used to measure the volume sampled to determine zooplankton catch per unit effort. Environmental variables such as water temperature, turbidity, secchi, and electrical conductivity are collected with each zooplankton sample. Concurrent fish and zooplankton tows conducted by STN and FMWT have allowed for comparisons of fish diet to the available zooplankton prey at the time of collection.
2021-2022 West False River Emergency Drought Barrier water quality, flow, and fish monitoring
To manage the critically low 2021 water supply for beneficial uses, DWR installed the temporary emergency drought barrier (EDB) on West False River in the Sacramento–San Joaquin Delta (Delta), approximately 5 miles south of Rio Vista, California, in Contra Costa County in June 2021. To monitor the effectiveness and impacts of the EBD, a monitoring program was initiated to track changes in hydrodynamics, water quality, fish, harmful algal blooms, and aquatic weeds in the vicinity of the EDB. The EDB was left in place during the winter of 2021-2022 and removed in fall of 2022. This data set includes all data collected as part of that monitoring program and subsets of ongoing monitoring programs that were used in the final effectiveness report for the EDB.
Sacramento-San Joaquin Bay-Delta Continuous (15 Minute) water quality monitoring data collected by the Continuous Environmental Monitoring Program, DWR, 2005- ongoing.
The Continuous Environmental Monitoring Program (CEMP) plays an instrumental role in overseeing real-time water quality in the Sacramento-San Joaquin Delta (the Delta) and Suisun Bay. The program harnesses wireless telemetry to transmit crucial data to the California Data Exchange Center (CDEC), making high-resolution environmental data pertaining to the Delta and Suisun Bay publicly accessible. The extensive dataset captures information at 15-minute intervals from 15 monitoring stations, utilizing YSI 6600 and YSI EXO sondes to obtain standalone water quality measurements. This extensive dataset informs the operations of the California State Water Project, ensuring it adheres to mandated water quality standards set by Water Right Decision 1641. This data compilation incorporates all information since the transition to YSI multiparameter sondes in 2005. It is important to note that the commencement dates and subsequent upgrades vary between stations, leading to slight discrepancies in the dataset's date ranges. Since its inception in the mid-1980s, CEMP has progressively expanded its monitoring capabilities, consistently augmenting the number of monitoring locations and the array of water quality parameters assessed. Its commitment to utilizing the most advanced water quality monitoring technology reaffirms its position as an environmental monitoring leader in the Delta and Suisun Bay. Today, the program oversees 15 water quality stations that reliably capture data every 15 minutes, each day of the year, transmitting this data in real-time. The core tenents of CEMP: • to obtain consistent and accurate data in real-time at established monitoring stations • to provide data necessary to achieve compliance with salinity, flow, and dissolved oxygen standards • to perform data analyses for further understanding of estuarine ecology • to report information to other government agencies, as well as the public, for the purpose of management and conservation of the upper San F
Interagency Ecological Program: Discrete water quality and phytoplankton data from the Sacramento River floodplain and Yolo Bypass tidal slough, collected by the Yolo Bypass Fish Monitoring Program, 1998 - 2022
The Yolo Bypass Fish Monitoring Program (YBFMP) operates a rotary screw trap and fyke trap and conducts biweekly beach seine and lower trophic surveys in addition to maintaining water quality instrumentation in the bypass. The YBFMP serves to fill information gaps regarding environmental conditions in the bypass that trigger migrations and enhanced survival and growth of native fishes, as well as provide data for IEP synthesis efforts. YBFMP staff also conduct analyses of YBFMP monitoring data to address pertinent management related questions as identified by IEP. The Yolo Bypass has been identified as a high restoration priority by the National Marine Fisheries Service and US Fish and Wildlife Service Biological Opinions for Delta Smelt, Winter and Spring-run Chinook salmon and by California EcoRestore. The YBFMP informs the restoration actions that are mandated or recommended in these plans and provides critical baseline data on the ecology of the bypass and how it interacts with the broader San Francisco Estuary. Program objectives include: Collecting baseline data on water quality, chlorophyll, lower trophic level biota, and fish in the Yolo Bypass to monitor spatial and temporal changes in trends and abundance; Analyzing and communicating Yolo Bypass data with stakeholders and the scientific and management communities to address pertinent management related questions; Providing technical expertise on Yolo Bypass aquatic ecology and monitoring and sampling methods. We collect discrete water quality data using a YSI ProDSS and sample phytoplankton, chlorophyll and nutrients as discrete water grabs taken biweekly (or weekly during Yolo Bypass inundation) along with lower trophic tows. Water is sampled at three sites along the Yolo Bypass and Sacramento River, then processed and analyzed by an internal DWR laboratory.
LAGOS-US LANDSAT: Data module of remotely-sensed water quality estimates for U.S. lakes over 4 ha from 1984 to 2020
This data package, LAGOS-US LANDSAT, is one of the extension data modules of the LAGOS-US platform that provides six water quality estimates (chlorophyll, Secchi depth, dissolved organic carbon, total suspended solids, turbidity, and true water color) from remote sensing for lakes ≥ 4 ha in the conterminous U.S. (48 states plus the District of Columbia) for the years 1984-2020. These estimates are generated through machine learning models on in-lake water quality matchups from LAGOS-US LIMNO with Landsat 5, 7, and 8 whole lake median reflectance values and pixel-wise band ratios that are subsequently used to make predictions across the U.S. The LANDSAT module contains remotely sensed reflectance values for 136,977 of the 137,465 lakes ≥ 4 ha from the LAGOS-US research platform. Within the module are a total of 45,867,023 sets of reflectance values, a matchup dataset with a window of up to 7 calendar days with in situ data, and associated water quality parameter predictions for each reflectance set. Additional quality control flags are provided for predictions indicating whether reflectance extractions included negative values, the percent of the maximum pixels ever retrieved for that lake that the predictions are based on, and whether there are shared calendar day predictions due to scene overlap.
The Jefferson Project 2021 water quality data from three vertical profiler stations in Lake George, NY, USA.
The Jefferson Project at Lake George -- a partnership between Rensselaer Polytechnic Institute, IBM Research, and Lake George Association -- combines Internet of Things technology and powerful analytics with science to create a new model for environmental monitoring and prediction. The project is building a computing platform that captures and analyzes data from a network of sensors tracking water quality and movement. These sensor data are combined with other monitoring and experimental data to create a thorough understanding of the factors that drive the lake's food web, hydrology, and water quality. More information about The Jefferson Project is available at https://jeffersonproject.rpi.edu/ In 2021, The Jefferson Project deployed three vertical profiler stations on the lake, collecting data on water quality and weather. Meteorological data have been included with the Jefferson Project Weather Station dataset for 2021. These vertical profiler stations are named VP_AnthonysNose, VP_HarrisBay, and VP_TeaIsland. The water quality data are collected by a YSI EXO2 Multi-parameter sonde sensors. The sensors collect data at 1 meter or less depth increments, starting at 1 meter and proceeding to 2 meters off bottom. The data are transferred in near real-time to an off-site database for monitoring and review. The data provided here have undergone data correction by Jefferson Project researchers.
The Jefferson Project 2021 hydrologic, water quality, and soil quality data from 12 Tributary Stations within the Lake George basin, NY, USA.
The Jefferson Project at Lake George -- a partnership between Rensselaer Polytechnic Institute, IBM Research, and Lake George Association -- combines Internet of Things technology and powerful analytics with science to create a new model for environmental monitoring and prediction. The project is building a computing platform that captures and analyzes data from a network of sensors tracking water quality and movement. These sensor data are combined with other monitoring and experimental data to create a thorough understanding of the factors that drive the lake's food web, hydrology, and water quality. More information about The Jefferson Project is available at https://jeffersonproject.rpi.edu/ In 2021, The Jefferson Project had twelve tributary monitoring stations around the lake collecting data on water quality, soil quality, and hydrology. These stations are TS_Finkle, TS_Hague, TS_Indian, TS_NorthwestBay, TS_Outlet, TS_PoleHill, TS_English, TS_Sunset, TS_Sucker, TS_ShelvingRock, TS_East, and TS_West. The stations have a sensor payload that may include some or all of the following sensors: YSI EXO2 Multi-parameter sonde, Campbell Scientific CS451 pressure transducer, SonTek-IQ+ multi-beam acoustic flow meter, Sontek-SL Doppler current meter, YSI WaterLOG® H-3123 submersible pressure transducer, and Stevens HydraProbe soil moisture sensor. The sensors collect data at high-frequency (~1 sample per minute) and the data are transferred in near real-time to off-site databases for monitoring and review by Jefferson Project researchers. The data provided here are level 4 data which underwent data correction and downsampling to an hourly frequency.
AquaMatch Chlorophyll a Data from Water Quality Portal: ~1970-2024
This dataset, “AquaMatch Chlorophyll a Data from Water Quality Portal ~1970-2024”, is a component of a forthcoming update to AquaSat (Ross et al., 2019), AquaSat version 2 (“v2”). The overarching purpose of AquaSat V2 is to emphasize the individual parts of the AquaSat pipeline that make-up the matchups between satellite and in-situ measurements. As such, we have greatly expanded and improved upon the AquaSat chlorophyll a dataset in two ways: First, we have incorporated additional recent in situ data beyond what was available at the publication of AquaSat. Second, we have created a data quality tiering system to provide end-users with more guidance on data usage. In this schema we have three tiers: restrictive data that are verifiably self-similar across organizations and time-periods and can be considered highly reliable; narrowed data that we have good reason to believe are self-similar, but for which we can not verify full compatibility across data providers; and inclusive data, which are assumed to be reliable and are harmonized to our best ability given the information available from the data provider. We have also added flag columns to help users understand complexities of the available depth and field sampling data. This dataset is a derived data product created using records downloaded from the Water Quality Portal (WQP) spanning January 6, 1970, to June 20, 2024. The WQP is a data warehouse for water-related data measured or observed within the United States and US Territories managed by the Environmental Protection Agency, United States Geological Survey, and the National Water Quality Monitoring Council. The dataset does not contain remote sensing matchups but can be paired with Landsat surface reflectances using the pipeline presented in Ross et al. (2019). Ross, M. R. V., Topp, S. N., Appling, A. P., Yang, X., Kuhn, C., Butman, D. et al. (2019). AquaSat: A data set to enable remote sensing of water quality for inland waters. Water Resources Research, 5
AquaMatch Dissolved Organic Carbon Data from Water Quality Portal: ~1970-2024
This dataset, “AquaMatch Dissolved Organic Carbon Data from Water Quality Portal ~1970-2024”, is a component of a forthcoming update to AquaSat (Ross et al., 2019), AquaSat version 2 (“V2”). The overarching purpose of AquaSat V2 is to emphasize the individual parts of the AquaSat pipeline that make-up the matchups between satellite and in-situ measurements. As such, we have greatly expanded and improved upon the AquaSat dissolved organic carbon dataset in two ways: First, we have incorporated additional recent in situ data beyond what was available at the publication of AquaSat. Second, we have created a data quality tiering system to provide end-users with more guidance on data usage. In this schema we have three tiers: restrictive data that are verifiably self-similar across organizations and time-periods and can be considered highly reliable; narrowed data that we have good reason to believe are self-similar, but for which we cannot verify full compatibility across data providers; and inclusive data, which are assumed to be reliable and are harmonized to our best ability given the information available from the data provider. We have also added flag columns to help users understand complexities of the available depth and field sampling data. This dataset is a derived data product created using records downloaded from the Water Quality Portal (WQP) spanning January 5, 1970, to June 27, 2024. The WQP is a data warehouse for water-related data measured or observed within the United States and US territories managed by the Environmental Protection Agency, United States Geological Survey, and the National Water Quality Monitoring Council. The dataset does not contain remote sensing matchups but can be paired with Landsat surface reflectances using the pipeline presented in Ross et al. (2019). Ross, M. R. V., Topp, S. N., Appling, A. P., Yang, X., Kuhn, C., Butman, D. et al. (2019). AquaSat: A data set to enable remote sensing of water quality for inland waters. Water
Missouri reservoir water quality data from the Statewide Lake Assessment Program (SLAP), the Lakes of Missouri Volunteer Program (LMVP), and the Reservoir Observer Student Scientists (ROSS) program
This dataset of limnological water quality data continues from Jones et al., 2024, starting in 2017 until 2021. It is from 195 reservoirs, the majority of which are in the state of Missouri (MO) in the USA collected by the University of Missouri Limnology Lab. Water quality parameters analyzed in the MU Limnology Lab during this time frame include: areal pigment absorption coefficient, alkalinity, alpha (light utilization efficiency P-E parameter), ammonium (NH4), ammonium-debt, anatoxin, chlorophyll a (corrected and uncorrected for pheophytins), chloride, cylindrospermopsin, seston d13C, seston d15N, dissolved turbidity, dissolved organic carbon, Ek (light saturation P-E parameter), FVFM (maximum quantum yield of PSII for photochemistry), gross primary production, microcystin, nitrate & nitrite (NO3), nitrate-debt, particulate nitrogen, particulate phosphorus, phosphorus-debt, pheophytin, particulate carbon, particulate inorganic matter, particulate organic matter, phycocyanin (PHYCO), saxitoxin, Secchi disk depth, silica, soluble reactive phosphorus, total dissolved nitrogen (TDN), total dissolved phosphorus (TDP), total nitrogen (TN), total phosphorus (TP), total suspended solids (TSS), and urea. Most of the samples were collected during the summer months (May-September) when the reservoirs were thermally stratified, but a few were taken during the rest of the year (October-April). The majority of samples were taken at the deepest point in the reservoir directly up-reservoir of the dam. Sampling was conducted from a boat most of the time, but a few samples were taken from shorelines and drinking water treatment intake pipes. Most of the data come from the Statewide Lake Assessment Project (SLAP) and the Lakes of Missouri Volunteer Program (LMVP) funded by the Missouri Department of Natural Resources. This data represents duplicate or triplicate water samples collected from either the water surface, integrated over the depth of the epilimnion, or from discrete dep
Missouri reservoir water quality data (2022 - current) from the Statewide Lake Assessment Program (SLAP)
This dataset of limnological water quality data continues from North et al., 2025, starting in 2022 until present. The data is from reservoirs, primarily within the state of Missouri (MO) in the USA collected by the University of Missouri Limnology Lab. Water quality parameters analyzed in the MU Limnology Lab during this time frame include: ammonium (NH4), anatoxin, chlorophyll a (corrected and uncorrected for pheophytins), chloride, cylindrospermopsin, dissolved organic carbon, microcystin, nitrate & nitrite (NO3), pheophytin, particulate inorganic matter, particulate organic matter, phycocyanin, saxitoxin, Secchi disk depth, total dissolved nitrogen (TDN), total dissolved phosphorus (TDP), total nitrogen (TN), total phosphorus (TP), total suspended solids, and urea. Most of the samples were collected during the summer months (May-September) when the reservoirs were thermally stratified, but a few were taken during the rest of the year (October-April). The majority of samples were taken at the deepest point in the reservoir directly up-reservoir of the dam. Sampling was conducted from a boat most of the time, but a few samples were taken from shorelines and drinking water treatment intake pipes. The bulk of the data come from the Statewide Lake Assessment Project (SLAP), funded by the Missouri Department of Natural Resources. This data represents duplicate or triplicate water samples collected from either the water surface, integrated over the depth of the epilimnion, or from discrete depths in the hypolimnion.
Continuous water quality measurements at Lindenwood Lake, Highlands Biological Station, Highlands, North Carolina, USA, 2022-2025
Measurements of turbidity, conductivity, dissolved oxygen, and water temperature were collected via an YSI EXO3 sonde in a 1.1 ha lake on the campus of Highlands Biological Station, Macon County, North Carolina. The sonde collects measurements every 15 minutes at a depth of ~0.5 m.
Daily Summary of Continuous water quality measurements at Lindenwood Lake, Highlands Biological Station, Highlands, North Carolina, USA, 2022-2025
Measurements of turbidity, conductivity, dissolved oxygen, and water temperature were collected via an YSI EXO3 sonde in a 1.1 ha lake on the campus of Highlands Biological Station, Macon County, North Carolina. The sonde collects measurements every 15 minutes at a depth of ~0.5 m.
Interagency Ecological Program: Fish catch and associated water quality for the Fall Midwater Trawl Survey, Sacramento-San Joaquin Delta, 1967-2024
The Interagency Ecological Program’s (IEP) Fall Midwater Trawl Survey (FMWT) is a long-term monitoring survey conducted by the California Department of Fish and Wildlife (CDFW) and has sampled annually since its inception in 1967, with the exceptions of 1974 and 1979, when sampling was not conducted. The FMWT was initiated to determine the relative abundance and distribution of age-0 Striped Bass (Morone saxatilis) in the San Francisco Estuary (California, United States), but the data has also been used for other upper estuary pelagic species, including Delta Smelt (Hypomesus transpacificus), Longfin Smelt (Spirinchus thaleichthys), American Shad (Alosa sapidissima), Splittail (Pogonichthys macrolepidotus), and Threadfin Shad (Dorosoma petenense). The FMWT currently samples 130 stations each month from September to December and a subset of this data is used to calculate an annual abundance index. These 130 stations range from San Pablo Bay upstream to Stockton on the San Joaquin River, and West Sacramento on the Sacramento Deep Water Ship Channel. FMWT sampling data includes 193 unique station locations throughout the San Francisco Estuary; 63 are not currently sampled. Most stations no longer sampled occur in South and Central San Francisco Bay (1968-1979), with others located in San Pablo Bay and upstream into the Delta. There are catch records for stations that were sampled only once. Data users are encouraged to look at station frequency over time to understand when and where sampling occurred. Sampling takes approximately 14 days per month to complete. Historically, FMWT sampling occasionally began as early as July (1972) or August (1968-1973, 1993-1994, 1996-1997) and sometimes continued past December to March (1968-1973, 1978, 1991-2001) or beyond (1992-1995). The Spring Midwater Trawl (SMWT) was a modified survey created to continue sampling January-March to track movements of mature adult delta smelt from 1991-2001. SMWT was replaced in 2002 with the more e
Characterization of Water Quality, Nutrients, and Algae Under Ice in the St. Louis River Estuary 2013 - 2018
This data package includes physical, chemical, and biological measurements characterizing under-ice and early open-water conditions in the St. Louis River Estuary—a freshwater estuary located at the western tip of Lake Superior. Data were collected annually during February and March from 2013 to 2018, with additional sampling in May and June 2018. Sampling sites were distributed across the estuary to assess spatial variability and investigate potential hypoxia. Field data include in situ water quality measurements (e.g., temperature, dissolved oxygen, conductivity, pH), light penetration, and snow and ice thickness. Laboratory analyses were conducted on collected samples to quantify nutrients, suspended sediment, and chlorophyll-a concentrations. Phytoplankton samples were collected using plankton nets and preserved in Lugol’s solution for taxonomic identification. Sampling and analysis followed EPA and USGS Standard Methods where applicable to ensure compatibility with other environmental datasets. This dataset fills a critical gap in winter limnology by providing rare observations of under-ice estuarine conditions. It supports ecological research, environmental monitoring, and comparative studies of seasonal dynamics, nutrient cycling, and primary producer communities in Great Lakes coastal wetlands and other northern freshwater systems. The dataset is complete and not ongoing, although data acquired through the System-wide Monitoring Program at the Lake Superior National Estuarine Research Reserve is complementary and ongoing.
ScienceDex guides
Understand access before you commit
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.