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.
19,393
datasets available to search
ShareScore release 0.7.1
Dataset results
19,393 results for “water”
Long-term trends in pesticide residues and physical chemical parameters of superficial water samples with accompanying macro-benthic invertebrate community surveys from the Palo Verde National Park, Costa Rica: 1993-1994; 2001; 2004-2005; 2009-2011
During the years 1993-1994, 2001, 2003-2005 and 2009-2011, the Central American Institute for Studies on Toxic Substances (IRET-UNA) executed independent research projects which quantified the presence of pesticide residues on superficial water samples from the Palo Verde National Park (PVNP) and surrounding areas. The PVNP (5460 sq km) is a RAMSAR wetland of international importance, which has been subjected to pesticide pressure from agricultural fields (mainly rice and sugarcane) since the 1960s and 1970s. In 1993, the PVNP wetlands were placed on the RAMSAR Montreux Record, indicating that it was considered an “impaired ecosystem” due to ecotoxicology concerns. Water is the key component of all issues regarding the biodiversity, management, restoration, and economic development of this region. Therefore, water quality is a critical component of many social ecological discussions and research efforts. This data package contains uniform pesticide, biological and water quality data from all PVNP wetland projects (1993- 2011) in order to present long-term trends in the environmental water quality and accompanying biological patterns for this conservation area. Study sites were spatially determined to compare clean upstream waters with a gradient of pesticide-affected waters. Superficial water samples were collected at various sites for chemical (pesticide) analysis and water quality parameters were recorded in situ for environmental monitoring. Corresponding biological sampling was completed to survey benthic macroinvertebrate communities and compare with local eco-toxicological profiles. This data package contains information from four separate projects.
Concentration of nutrients in water samples collected from the Upper Clark Fork River (Montana, USA) during water year 2019 (1 Oct 2018 - 30 Sept 2019)
The umbrella LTREB monitoring project generating these data is conducted separately and complementarily to the $200 million-dollar (USD) superfund project for ecological restoration of the Upper Clark Fork River (UCFR), associated tributaries, and head water streams including Silver Bow and Warm Springs Creeks. Restoration along the Upper Clark Fork River includes removal of metal-laden floodplain soils, lowering of the floodplain to its original elevation, and re-vegetation of over 70 km of the river's floodplain closest to contaminant sources. The UCFR Long Term Research in Environmental Biology (LTREB) project includes bi-weekly water quality monitoring across a 200-km gradient of heavy metal contamination associated with historic mining. Monitoring includes inorganic phosphorus and nitrogen concentrations, biotic standing stocks, and dissolved and whole-water heavy metal concentrations. The UCFR LTREB monitoring project is conducted within the first 200 km of the Upper Clark Fork River and associated tributaries located in western Montana. The current monitoring program began in 2017 and will be completed in the year 2023, with likely funding extension to 2028. Surface water samples represented in this data product are collected from fourteen sites along the mainstem of the UCFR, and one site representing a major tributary to the UCFR. Water samples are collected at each monitoring site in triplicate and filtered with a 0.7-µm glass fiber filter. Nutrient samples are analyzed using a spectrophotometric flow injection analyzer (AP2) for nitrate (NO3-N), soluble reactive phosphorus (SRP, as representative of PO4-P), and ammonium (NH4-N) concentrations reported in mg/L. The analysis-ready data of this dataset therefore represent Quality Assurance and Quality Control (QAQC) processed NH4-N, SRP, and NO3-N concentrations from fourteen sites along the mainstem of the UCFR and one tributary, collected in water year 2019 (1 Oct 2018 - 30 Sept 2019).
Discrete water temperature, flow, solar radiation, chlorophyll-a and inundation, Sacramento-San Joaquin Delta, CA, 1999-2019
The objective of our study is to better understand the factors affecting chlorophyll-a production within a floodplain and its transport downstream to determine how lateral connectivity influences longitudinal connectivity. The Yolo Bypass is an engineered floodplain of the Sacramento River that inundates during periods of high outflow via overtopping weirs. Water traveling through the Yolo Bypass flows parallel to the Sacramento River and re-connects to the mainstem at the southern extent of the floodplain. Several monitoring programs in the Sacramento San-Joaquin Delta and Yolo Bypass collect discrete and continuous water quality data, including chlorophyll measurements. For this study, we synthesized available flow, water temperature, chlorophyll and inundation data between March 1999 to December 2019 and modeled the effects of environmental variables and inundation on chlorophyll-a production in the floodplain, the mainstem, and downstream of the floodplain/mainstem.
Water Monitoring of the Choptank River and Pocomoke River, Maryland, USA
Water monitoring at four locations on the Choptank River and four locations on the Pocomoke River in Maryland, U.S.A., was conducted from 2021 through 2023. Funding and scientific rationale were provided by the National Science Foundation grant 2049073 (“Resolving Sediment Connectivity between Rivers and Estuaries by Tracking Particles with their Microbial Genetic Signature”). The monitoring locations were chosen to measure estuary dynamics from the tidal freshwater zone through the mesohaline estuary. Parameters measured included water temperature, water level, water conductivity (reported as specific conductivity), water turbidity, and water velocity.
State Water Project, Genetic Determination of Population of Origin 2011-2024
Central Valley Chinook Salmon populations differ in their Endangered Species Act listing status. It is often difficult to distinguish individuals from the different Evolutionarily Significant Units. As such, many of the salmon monitoring and evaluation efforts in the Central Valley and San Francisco Bay-Delta are hampered by uncertainty about population (stock) identification and proportional effects of management actions (Dekar et al. 2013; IEP 2019). Studies have identified that the current identification method (length-at-date models) of juvenile Chinook salmon (Fisher 1992) captured in the watershed vary in their accuracy, particularly for spring-run (NMFS 2013; Harvey et al. 2014; Merz et al. 2014). The inaccuracy of the size-based methods is likely due to differences in fish distribution during early rearing, habitat-specific growth rates, and inter-annual variability in temperatures and food availability that lead to overlap in size ranges among stocks. The primary objective of this project was the genetic classification (to race; Evolutionary Significant Unit) of Chinook Salmon captured from State Water Project and Central Valley Project fish protection facilities and Interagency Ecological Program monitoring programs. The population-of-origin was determined for sampled fish by comparing their genotypes to reference genetic baselines. Genetic methods, having less statistical uncertainty that size-based models for population identification, were intended to directly target (and reduce) one source of uncertainty in the estimation of loss (take) from water diversions (operations) and develop the information necessary for understanding stock-specific distribution, habitat utilization, abundance, and life history variation. This project supports recommendations from the Interagency Ecological Program’s Salmon and Sturgeon Assessment of Indicators by Life Stage and Interagency Ecological Program Science Agenda efforts to improve Central Valley salmonid monitoring
Code for Random Forest models that predict pharmaceutical and water chemistry measurements in Baltimore Ecosystem Study streams
This file contains code to model the relationship between the water chemistry measurements and discharge measured as part of BES routine sampling and the pharmaceuticals measured in WY 2018. We use Random Forest models to predict 1) total (i.e., summed) concentration of the pharmaceuticals for which we screened, 2) total nutrient concentrations (TN & TP), 3) whether or not the antibiotic trimethoprim was detected in a given sample, and 4) whether or not nitrate and TP were above or below environmentally-relevant threshold concentrations. We also use RF models to predict N and P concentrations over a longer period, in order to compare models for nutrients to pharma. Code and analyses here rely on data processed in the file "BESPharma_WY2018.Rmd", published on EDI (doi:10.6073/pasta/610cb67fcbc8982c2af8ed946dce8ea5) and BES water chemistry data published on EDI (doi:10.6073/pasta/ce7f30e6013e003bfe28c5fd7d4aed23 )
Great Bay Estuary, NH/ME, Box Model Water Chemistry, Flow, Precipitation, and Seagrass Coverage Data, 2008 - 2023.
This data repository contains compiled surface water (tributary and estuarine), wet deposition, and wastewater effluent chemistry, along with discharge, precipitation totals, and monthly effluent flows necessary for the completion of solute budgets for Great Bay, a subregion of Great Bay Estuary, NH/ME, USA. These datasets are part of on-going monitoring programs in the Great Bay Estuary and Lamprey River Hydrological Observatory. A subset of the monitoring data for the 2008 to 2023 period was compiled. The tributary and estuarine monitoring data were requested from the NH Department of Environmental Services Environmental Monitoring Database as part of the Tidal Tributary and Estuary Water Quality Monitoring Programs. The wet deposition chemistry record is maintained as part of the Lamprey River Hydrologic Observatory. Wastewater effluent chemistry was downloaded from the EPA's Enforcement and Compliance History Online Database. The annual (1996 - 2023) seagrass coverage dataset for Great Bay Estuary reflects coverage of Zostera marina seagrass only and was compiled from annual monitoring reports. Mean daily instantaneous discharge data for the three tidal tributaries used in the load calculations are available from the USGS National Water Information System. Hourly precipitation volume data for the Durham, NH SSW station are available from the NCDC U.S. Climate Reference Network, with minor hourly gaps filled using the University of New Hampshire Durham weather station (https://www.weather.unh.edu).
Water temperature in the hidden, subglacial lake at Uruguay Island, Antarctic Peninsula region, 2020-2021, and additional data sets.
The dataset contains temperature measurements in a small subglicer (hidden) lake of Antarctic Peninsula region at several levels of depth. The measurements cover almost a full year and provide an understanding of the temperature and hydrological regime of the water body. Weather measurement data and statistics is provided additionally.
High-Frequency and Water Quality Monitoring Data of Long Pond at Grafton Lakes State Park, New York, United States, 2024
This collection of datasets contains high frequency data captured through Hobo, Minidot, and water level sensors, as well as data collected from manual sampling days. Long Pond is located in Grafton New York, USA named for its long shape and shallower depth (max depth is around 8 meters). Using a buoy, sensors were attached to a rope at the deepest point discoverable and deployed. Data covers all information recorded from 2024-04-30 to 2024-10-09. Times are recorded in Eastern Standard Time. Temperature Readings were taken every 10 minutes at 1 meter intervals by both Minidots and hobo sensors (1.52-7.52 m). Dissolved Oxygen was similarly collected every 10 minutes by the Minidots at depths 1.52, 6.52, and 7.52 meters. Manual measurements (YSI and Secchi disk) were recorded on sampling days, as well as water samples that were assessed for water quality parameters from the top and bottom of the lake. Water level data was also collected in 12 hour intervals.
Water quality in restored urban streams in Lexington, KY, USA
Stream-water grab samples were collected periodically from sampling locations upstream and downstream of restored stream reaches in Lexington, KY, USA, and analyzed for a suite of water quality characteristics including nitrate, cations, and pH. Study sites included streams receiving riparian reforestation or other conservation, as well as streams restored using a natural channel design approach. The goal of this sampling program was to evaluate to what extent stream restoration interventions can influence stream-water quality in an urban context.
Nearshore high-frequency temporal water quality observations and process-based modeling of aquatic ecosystem metabolism in Lake Tahoe completed by members of the Blaszczak Lab at the University of Nevada Reno, 2021-2023
The overarching goal of this project was to develop a process-based understanding of how watershed-to-lake connections drive nearshore productivity dynamics in a large oligotrophic mountain lake (Lake Tahoe). We addressed this goal through a combined approach of high-frequency sensor deployment and maintenance, ecosystem metabolism modeling, laboratory incubations, and routine monitoring of water chemistry and other parameters. The data we collected as part of this project and the ecosystem metabolism estimates we generated demonstrate how variable ecosystem productivity is in time and space in the nearshore of Lake Tahoe. Although maintenance of the sensor arrays during the exceptional winter of 2023 was challenging, we were able to capture the data necessary to estimate a complete time series of metabolic activity across two years with very different hydroclimatic conditions. Throughout this project we accomplished the following: 1. We generated over two years of daily estimates of ecosystem metabolism (gross primary productivity, ecosystem respiration, and net ecosystem productivity) from multiple locations on both the east and west shores of the lake and from areas in close proximity to and far away from stream water inflows. 2. We measured ammonium (NH4+) and nitrate (NO3-) concentrations in surface water samples from both Glenbrook and Blackwood creeks and the nearshore of Lake Tahoe for over two years. 3. We quantified rates of NH4+ and NO3- uptake in benthic samples of the dominant substrate type collected during peak streamflow, the receding limb, and baseflow conditions in 2023 from multiple locations in the nearshore using established laboratory incubation methods. 4. Finally, we used a combination of time series models and structural equation modeling to integrate our results and improve understanding of the direct and indirect effects of hydroclimatic variability on observed patterns in ecosystem metabolism in the nearshore. See this git code repository
Longitudinal water quality sampling of King's Creek (KS) and Caribou Creek (AL), 2022 and 2023
We sampled Caribou Creek in July 2022 and King's Creek in August 2022 and May 2023 longitudinally for dissolved carbon dioxide using a headspace equilibrium method as well as other water quality parameters. The data was used to inform a stream network model to model carbon dioxide across the stream networks. The data package is complete.
Water chemistry time series for Beaverdam Reservoir, Carvins Cove Reservoir, Falling Creek Reservoir, Gatewood Reservoir, and Spring Hollow Reservoir in southwestern Virginia, USA 2013-2024
Depth profiles of dissolved organic and inorganic carbon and total and dissolved nitrogen and phosphorus were sampled from 2013-2024 in five drinking water reservoirs in southwestern Virginia, USA. The five drinking water reservoirs are: Beaverdam Reservoir (Vinton, Virginia), Carvins Cove Reservoir (Roanoke, Virginia), Falling Creek Reservoir (Vinton, Virginia), Gatewood Reservoir (Pulaski, Virginia), and Spring Hollow Reservoir (Salem, Virginia). Beaverdam, Carvins Cove, Falling Creek, and Spring Hollow Reservoirs are owned and operated by the Western Virginia Water Authority as primary or secondary drinking water sources for Roanoke, Virginia, and Gatewood Reservoir is a drinking water source for the town of Pulaski, Virginia. The dataset consists of depth profiles of water chemistry samples measured at the deepest site of each reservoir adjacent to the dam. Additional water chemistry samples were collected at a gauged weir on Falling Creek Reservoir's primary inflow tributary, as well as multiple upstream, inflow, and outflow sites at Falling Creek Reservoir 2014-2024 and Beaverdam Reservoir in 2019, 2020, and 2022. Inflow sites at Carvins Cove Reservoir were sampled from 2020-2024, and additional within-reservoir sites were sampled in 2021-2024. The water column samples at Falling Creek Reservoir and Beaverdam Reservoir were collected approximately fortnightly from March-April, weekly from May-October, and monthly from November-February. Water column samples at Carvins Cove Reservoir were collected approximately fortnightly from May-August in most years, and approximately fortnightly from 2014-2016 in Gatewood and Spring Hollow Reservoirs, though sampling frequency and duration varied among reservoirs and years. A few additional samples collected in 2025 from Falling Creek Reservoir and Carvins Cove Reservoir are included in this dataset as they were analyzed with 2024 samples.
Nutrient amendment effects on phytoplankton, water chemistry, and cyanotoxins in the 2018 Large-Scale Mesocosm Experiment at the University of Kansas Field Station
This dataset includes water physicochemical parameters, phytoplankton community composition, and cyanobacteria metabolites collected during a 21-day nutrient amendment experiment conducted from 23 July to 13 August 2018 at the University of Kansas Biological Station, Lawrence, KS, United States (39.049674°N, 95.190777°W). The experiment was performed using 18 large-scale, closed-bottom fiberglass tanks (volume: 11,000 L; height: 1.25 m; diameter: 3 m). Three tanks served as ambient controls (CON), while the others received one of the following nutrient treatments: nitrogen only (280 µM) as either ammonium chloride (NH4) or sodium nitrate (NO3); nitrogen (280 µM) plus phosphorus (200 µM) as either ammonium chloride + dipotassium phosphate (NHP) or sodium nitrate + dipotassium phosphate (NOP); and phosphorus only (200 µM) as dipotassium phosphate (P). Each tank received an initial nutrient dose on Day 0.5, followed by weekly additions of 20% of the initial amendment to maintain treatment conditions. All data were quality controlled to correct basic errors and to remove measurements outside the manufacturer’s standard operational ranges.
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.
Indicators of Contaminant Sources, PFAS, and Water Quality in Ellerbe Creek and New Hope Creek, NC (2019-2022)
Thousands of chemical contaminants are found in urban stream globally. This is a dataset of water quality measures of (1) compounds that are indicative of specific contaminant sources, (2) common water quality measures [trace metals, major ions, nutrients], and (3) PFAS. Sampling was conducted in Ellerbe Creek and New Hope Creek in the Durham and Orange counties of North Carolina. Biweekly and synoptic sampling was undertaken to explore spatial and temporal variation in water concentrations.
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.