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162 results for “Water quality data”
Big Spirit Lake Monitoring Buoy: High Frequency Oxygen, Temperature, Water Quality and Weather Data 2020-2021
High frequency weather and limnological data from the Big Spirit Lake monitoring buoy, Iowa, USA, from 2020 - 2021. The Big Spirit Lake (Global Lake Ecological Observatory Network—GLEON) instrumented monitoring buoy is operated by the Iowa Lakeside Laboratory (https://iowalakesidelab.org/). The buoy is equipped with a thermistor chain and dissolved oxygen probes the measure every meter from 1m to 6m in depth, a multi-parameter sonde at 1 meter depth, as well as a weather station and wave sensor (added in 2021) situated on the buoy. All data in this data package have been QAQC'd to remove obviously errant readings, highly suspicious readings, and artifacts of buoy maintenance. Because of this, as well as sensor errors and failure, not all data is available at every point each year. Measured parameters in the data set include water temperature, dissolved oxygen concentration, and dissolved oxygen saturation (measured every meter from 1m to 6m). Other measured parameters include pH, specific conductivity, chlorophyll, and blue-green algae in the surface water, as well as weather station data and wave sensor data. Sampling Frequency: Parameters are measured at 10 minute intervals, and most years include measurements from mid/late May through October.
West Okoboji Lake Monitoring Buoy: High Frequency Oxygen, Temperature, Water Quality and Weather Data 2015-2021
High frequency weather and limnological data from the West Okoboji Lake monitoring buoy, Iowa, USA, from 2015 - 2021. The West Okoboji Lake (Global Lake Ecological Observatory Network—GLEON) instrumented monitoring buoy is operated by the Iowa Lakeside Laboratory (https://iowalakesidelab.org/). The buoy is equipped with a thermistor chain and dissolved oxygen probes the measure every 2 meters from 1m to 25m in depth, a multi-parameter sonde at 1 meter depth, as well as a weather station situated on the buoy. All data in this data package have been QAQC'd to remove obviously errant readings, highly suspicious readings, and artifacts of buoy maintenance. Because of this, as well as sensor errors and failure, not all data is available at every point each year. Measured parameters in the data set include water temperature, dissolved oxygen concentration, and dissolved oxygen saturation (measured every 2 meters from 1m to 25m). Other measured parameters include pH and specific conductive in the surface water, as well as weather station data including wind, rain, air temperature and humidity. Sampling Frequency: Parameters are measured at 10 minute intervals, and most years include measurements from mid/late May through October. Measurements were stopped in the fall once the lake had turned over.
LAGOS Lake nutrient, carbon and chlororphyll data to evaluate biases in lake water quality sampling practices in a 17-state region of the US
This dataset includes data for eight major limnological variables in LAGOS-NE_LIMNO v. 1.087.1 that were used to evaluate biases in lake water quality sampling and implications for macroscale research (Stanley et al. In Revision, Limnology and Oceanography). Most observations came from LAGOS-NE_LIMNO v. 1.087.1, an integrated database of lake ecosystems (Soranno et al. 2015, Soranno et al. 2017) but were supplemented with additional data from the State of New Hampshire. LAGOS-NE contains information on lakes great than or equal to 1 ha (originally derived from the U.S. Geological Survey's 2013 National Hydrography Dataset) for a 17-state region of the U.S., and a subset of the lakes has observational data on lake chemistry and productivity. Approximately 87 different sources of data were compiled for the LAGOS-NELIMNO v. 1.087.1 dataset and were mostly generated by government agencies (state, federal, tribal) and universities. In this analysis, we compiled data for eight major limnological variables (Secchi disk depth, chlorophyll, total phosphorus, total nitrogen, nitrate, ammonium, true water color, and dissolved organic carbon) and geographic characteristics of lakes (location, lake area, depth, perimeter, watershed area) to evaluate biases in different limnological properties over space and time.
Water Quality Data from Bethel and Stephens Lakes, Columbia, Missouri 2017-2019
This data set encompasses approximately weekly to biweekly water quality samples from Bethel and Stephens Lakes in Columbia, Missouri. The samples were collected as part of the Reservoir Observer Student Scientists Program to examine year-round water quality parameters in these urban reservoirs. Samples were collected by high school students, college students, and staff of the University of Missouri Limnology Laboratrory. Six samples at Stephens Lake were collected by volunteer community scientists as part of the Lakes of Missouri Volunteer Program. Bethel Lake was sampled November 2017 through November 2019, and Stephens Lake was sampled November 2018 through November 2019. Temperature data was obtained from Onset HOBO temperature data loggers that were deployed in 0.5-m increments from the bottom of the reservoirs to within 1 m of the surface.
Hedonic Modeling Data for Land Use Regulations and Water Quality in Buncombe County, N.C.
The State of North Carolina's Water Supply Watershed Protection Act of 1989 required local governments to adopt land use measures selected watersheds to protect the water supply emanating from those watersheds. We examine vacant land prices in and around the Ivy River watershed of Buncombe County, NC, at the time such regulation took effect in 1998. Our results suggest that costs of watershed development restrictions are borne primarily by those vacant land owners in the watershed for whom the development restrictions make land subdivision infeasible. We find benefits accruing to land owners on the public water supply or who are adjacent to creeks.
Water Quality of Virginia Coastal Bays - physical data 1992-2008
This dataset has been superceded by: VCR15243 Water Quality Sampling - integrated measurements for the Virginia Coast, 1992- Please see that dataset for updated data.
Data Sets: An Assessment of Water Trusts: Drinking Water Quality and Provision in Six Low-income, Peri-urban Communities of Lusaka, Zambia
<p>Data set associated with the manuscript published in GeoHealth titled An Assessment of Water Trusts: Drinking Water Quality and Provision in Six Low-income, Peri-urban Communities of Lusaka, Zambia. This includes bacterial, nitrate, specific conductance, and Water Trust survey data collected from Lusaka, Zambia in 2013, 2014, 2016, an 2019.</p>
Littoral macroinvertebrate and water quality data for 32 lakes across the boreal-tundra transition in the Northwest Territories
<p>This dataset includes macroinvertebrate and water quality data from 32 lakes sampled in the Northwest Territories, Canada, from the Dempster and Inuvik-Tuktoyaktuk Highways during July and August of 2017 and 2018. It was collected as part of a project to determine how physicochemical variables affect macroinvertebrate and fish communities in small Arctic lakes.</p>
Water quality data sets of the Gozyo catchment and the four U.S. watersheds
<p>This zipped file contains three excel files. Table GZ_Solute.xls and Table GZ_Tb.xls are high-frequency water quality data in the stream of the small forested catchment, Gozyo cattchment (12.14ha), Nara, Japan. The high-frequency on-site Water quality (WQ) measurements of K, Cl, and Na in the stream using flow-injection potentiometry method with 15-minute interval were interpolated to 10-minute interval data. The SS concentration in the stream was estimated by linear transformation from the observed 10-minute turbidity value. Table GZ_Solute.xls gives observed 10-minute solutes data with discharge, rainfall, and temperature from 2009 to 2011, and Table GZ_Tb.xls provides the observed 10-minute turbidity data from 2012 to 2014. SS value (mg/l) is calculated as 1.09 Turbidity + 6.19. The data value of -999 means missing observation.</p> <p>Tables US_daily_WQ_datasets.xls contains daily water quality (WQ) and discharge data from the four watersheds in the United States. The data value of -999 also means missing observation. The names (USGS station numbers) of four WQ monitoring sites are Muskingum River (03150000), Rock Creek (04197170), Skunk River (05474000), and Vermilion River (04195000). Daily WQ data were composed by following the procedure described in the Appendix S1 in Hirsch (2014). The WQ data for Muskingum, Rock, and Vermilion river were retrieved from Heidelberg University's National Center for Water Quality Research site (https://ncwqr.org/monitoring/data) and suspended sediment discharge data were downloaded from the USGS National Water Information System (<a href="http://waterdata.usgs.gov/nwis/">http://waterdata.usgs.gov/nwis/</a> or https://doi.org/: 10.5066/F7P55KJN). All the daily discharge data were acquired via the USGS National Water Information System.</p> <p>These data were used to evaluate the performance of the unbiased load estimates and confidence intervals of river loads based on the Rating curve method using importance sampling in the listed article below. To maintain the traceability of the proposed load estimation method and replicability the results in the article, the authors of the article upload the data used in this repository.</p> <p> </p> <p>References</p> <p>Hirsch, R. M. (2014). Large biases in regression-based constituent flux estimates: causes and diagnostic tools. <em>Journal of the American Water Resources Association</em>, 50(6), 1401-1424. https://doi.org/10.1111/jawr.12195</p> <p>Tada, A. and H. Tanakamaru. (Submitted) Unbiased estimates and confidence intervals for riverine loads, <em>Water Resources Research</em>.</p>
Zooplankton and water quality data for 37 lakes in the Gwich'in and Inuvialuit regions of the Northwest Territories
<p>This dataset includes zooplankton and water quality data from 37 lakes sampled in the Northwest Territories, Canada, from the Dempster and Inuvik-Tuktoyaktuk Highways during July and August of 2017 and 2018. It was collected as part of a project to determine how physicochemical variables affect zooplankton and fish communities in small Arctic lakes.</p>
Consumer value data for water quality improvement depending on the gap between perceived and expected condition
<p>This CSV file provides data from a survey of consumers about the gap between current and expected tap water quality. The WTP analysis of consumers' expectations for improved tap water quality was estimated with the R program. The R program is available at https://www.r-project.org.</p>
Monthly city-level water quality data of China from 2014 to 2020.
Open the record for dataset details and reuse information.
Global Water Quality Data: Historical Nitrogen and Phosphorus Loads and Concentrations Simulated by CoSWAT-WQ v1.0
<p>Output data on global TN and TP water quality and scripts for the historical period (1995 - 2016) generated by CoSWAT-WQ v1.0. Please check the readme file for data description. The data includes river flow, , nitrogen and Phosphorus loads and concetrations at monthly timestep.</p>
Satellite-derived water quality data for Lake Harsha (USA) 2015-2019
This dataset contains satellite-derived water quality (WQ) data of Lake Harsha (USA) for the years 2015-2019. Available parameters are: Total Absorption (ABS), Chlorophyll-a (CHL), Harmful Algae Bloom Indicator (HAB), True-color image (RGB), Secchi Disc Depth (SDD), Sea Surface Temperature (SST), Total Suspended Matter (TSM) and Turbidity (TUR). WQ parameters have been calculated using EOMAPs physics-based MIP from Sentinel-2 and Landsat 8. The data are available as GeoTiff files in web-mercator projection (EPSG: 3857). Further information can be found in the readme files. Contains Copernicus data. Credits: ESA (2022). Landsat data courtesy of the United States Geological Survey (2022).
Satellite-derived water quality data for Lake Hume (Australia) 2015-2019
<p>This dataset contains satellite-derived water quality (WQ) data of Lake Hume (Australia) for the years 2015-2019. Available parameters are: Total Absorption (ABS), Chlorophyll-a (CHL), Harmful Algae Bloom Indicator (HAB), True-color image (RGB), Secchi Disc Depth (SDD), Sea Surface Temperature (SST), Total Suspended Matter (TSM) and Turbidity (TUR). WQ parameters have been calculated using EOMAPs physics-based MIP from Sentinel-2 and Landsat 8. The data are available as GeoTiff files in web-mercator projection (EPSG: 3857). Further information can be found in the readme files. Contains Copernicus data. Credits: ESA (2022). Landsat data courtesy of the United States Geological Survey (2022).</p>
Satellite-derived water quality data for Western Water Treatment Plant (Melbourne, Australia) 2015-2019
This dataset contains satellite-derived water quality (WQ) data of Western Water Treatment Plant (Melbourne, Australia) for the years 2015-2019. Available parameters are: Total Absorption (ABS), Chlorophyll-a (CHL), Harmful Algae Bloom Indicator (HAB), True-color image (RGB), Secchi Disc Depth (SDD), Total Suspended Matter (TSM) and Turbidity (TUR). WQ parameters have been calculated using EOMAPs physics-based MIP from Sentinel-2. The data are available as GeoTiff files in web-mercator projection (EPSG: 3857). Further information can be found in the readme files. Contains Copernicus data. Credits: ESA (2022).
Satellite-derived water quality data for Lake Mulargia (Sardinia, Italy) 2015-2019
This dataset contains satellite-derived water quality (WQ) data of Lake Mulargia (Sardinia, Italy) for the years 2015-2019. Available parameters are: Total Absorption (ABS), Chlorophyll-a (CHL), Harmful Algae Bloom Indicator (HAB), True-color image (RGB), Secchi Disc Depth (SDD), Sea Surface Temperature (SST), Total Suspended Matter (TSM) and Turbidity (TUR). WQ parameters have been calculated using EOMAPs physics-based MIP from Sentinel-2 and Landsat 8. The data are available as GeoTiff files in web-mercator projection (EPSG: 3857). Further information can be found in the readme files. Contains Copernicus data. Credits: ESA (2022). Landsat data courtesy of the United States Geological Survey (2022).
Data from: Improving governance outcomes for water quality: insights from participatory social network analysis for chalk stream catchments in England
<p>Globally important chalk streams in England are in poor ecological health, in part due to inadequate water quality. Addressing this issue requires an understanding of the governance systems that surround water quality. The complexity and uncertainty inherent in hydrological systems has led to the emergence of integrated and adaptive forms of governance. In these multi-actor governance systems, the structure of the relationships between actors (the social network) has been shown to affect governance processes and outcomes.</p> <p>Using participatory social network analysis, we mapped and analysed the social networks for the River Test and River Itchen in Hampshire, UK, to identify actors and their roles, determine the network characteristics, and identify interventions to improve governance.</p> <p>Although the results suggest a well connected network of actors from the state, private sector and civil society, we find that decision making is not decentralised. Bureaucratic governance by central state actors dominates. However, trust in these central state actors and private actors in the networks is low, which undermines collaboration and co-ordination in the network.</p> <p>Devolving authority to local actors, building trust in the networks, and improving connections to important actors could help to improve governance outcomes for water quality.</p>
Data: Water quality and the biodegradability of dissolved organic carbon in drained boreal peatland under different forest harvesting intensities
<p><span>This repository consists of three files, which contain ground water and ditch water quality data in drained forested peatlands and dissolved organic carbon biodegradation to carbon dioxide. Experiments and results are presented in:</span></p> <p><span>Palviainen M., Peltomaa E., Laurén A., Kinnunen N., Ojala A., Berninger F., Zhu X., Pumpanen J. 2022. Water quality and the biodegradability of dissolved organic carbon in drained boreal peatland under different forest harvesting intensities. Science of the Total Environment 806: 150919 <a href="https://doi.org/10.1016/j.scitotenv.2021.150919">https://doi.org/10.1016/j.scitotenv.2021.150919</a>.</span></p> <p><span> </span></p>
Urban stormwater pond water quality and vegetation cover data
<p>These data include measurements of water physical and chemical parameters and littoral vegetation measurements in urban stormwater ponds located in three different urban land use types in Orlando, Florida, USA.</p>
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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.