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484 results for “water quality”
Simulated submerged aquatic vegetation spectral signatures under different water quality conditions using Hydrolight
<p>Reflectance spectra were simulated using the Hydrolight radiative transfer model (Sequoia Scientific, Bellevue, WA) for four different submerged macrophyte species under a range of water quality conditions at two different depths. We used the four-component case-2 model with spectral reflectance of four submerged species, Egeria densa, Ceratophyllum demersum, Cabomba caroliniana, and Stukenia pectinata. These four reflectance spectra were calculated from the median of 10 measurements of the canopies of the representative species placed in clear tap-water made with a handheld ASD FieldSpec Pro spectrometer. Total suspended solids concentration was varied from 1 to 40 g·m<sup>−3</sup>, chlorophyll-a concentration was varied from 0.5 to 50 mg·m<sup>−3</sup>, and colored dissolved organic matter (CDOM) was varied from 0.25 to 3.5 m<sup>−1</sup>. A total of 4,742 spectra were simulated for all four species and a mud substrate at two different depths, 1 m and 5 m, and for optically deep water.</p>
Measuring water quality parameters to estimate Nitrate concentration in surface water in Bonet catchment, Sligo, Ireland
<p><span>Time series data of surface water quality (temperature, pH, dissolved oxygen, oxidation-reduction potential and electrical conductivity) collected from May 2024 to September 2024 at 1m intervals. The file contains tabular data with the following columns: Date and time, Battery (%), temperature (ºC), fix Quality in fix code (Fix), Latitude (in deg), Longitude (in deg), pH,<span> </span>electrical conductivity (µS/cm), TDS (in ppm),<span> </span>Salinity in PSU(ppt), Specific Gravity (in SG), Dissolved Oxygen (in mg/L), Oxygen Saturation (in %), ORP (in mV), Altitude (in meters), Ground Speed (in m/s), Horizontal dilution, Satellites in number.</span></p>
PRISMA-derived water quality parameters for Lake Hume (Australia) (2020/04/22)
<p>This dataset contains PRISMA-derived water quality (WQ) products of Lake Hume (Australia) for the 22 April 2020. Available parameters are: True-color image (RGB), Colored Dissolved Organic Matter (CDOM), Chlorophyll-a (CHL), and Suspended Particulate Matter (SPM). WQ parameters have been calculated using CNR’s bio-optical model BOMBER parameterized with the inherent optical properties specific of the case study. The data are available as GeoTiff files in WGS 84 / UTM zone 32N (EPSG: 32632). PRISMA data courtesy of the Italian Space Agency (ASI, 2020).</p>
DESIS-derived water quality parameters for Lake Hume (Australia) (2020/02/26)
<p>This dataset contains DESIS-derived water quality (WQ) products of Lake Hume (Australia) for the 26 February 2020. Available parameters are: True-color image (RGB), Colored Dissolved Organic Matter (CDOM), Chlorophyll-a (CHL), and Suspended Particulate Matter (SPM). WQ parameters have been calculated using CNR’s bio-optical model BOMBER parameterized with the inherent optical properties specific of the case study. The data are available as GeoTiff files in WGS 84 / UTM zone 32N (EPSG: 32632). DESIS data courtesy of the German Aerospace Center (DLR, 2020).</p>
DESIS-derived water quality parameters for Lake Mulargia (Sardinia, Italy) (2020/08/17)
<p>This dataset contains DESIS-derived water quality (WQ) products of Lake Mulargia (Sardinia, Italy) for the 17 August 2020. Available parameters are: True-color image (RGB), Colored Dissolved Organic Matter (CDOM), Chlorophyll-a (CHL), and Suspended Particulate Matter (SPM). WQ parameters have been calculated using CNR’s bio-optical model BOMBER parameterized with the inherent optical properties specific of the case study. The data are available as GeoTiff files in WGS 84 / UTM zone 32N (EPSG: 32632). DESIS data courtesy of the German Aerospace Center (DLR, 2020).</p>
PRISMA-derived water quality parameters for Lake Mulargia (Sardinia, Italy) (2020/07/08)
<p>This dataset contains PRISMA-derived water quality (WQ) products of Lake Mulargia (Sardinia, Italy) for the 8 July 2020. Available parameters are: True-color image (RGB), Colored Dissolved Organic Matter (CDOM), Chlorophyll-a (CHL), and Suspended Particulate Matter (SPM). WQ parameters have been calculated using CNR’s bio-optical model BOMBER parameterized with the inherent optical properties specific of the case study. The data are available as GeoTiff files in WGS 84 / UTM zone 32N (EPSG: 32632). PRISMA data courtesy of the Italian Space Agency (ASI, 2020).</p>
Dataset of water quality parameters (WP6 Cure4Aqua)
<p>Dataset of water quality parameters (alkalinity, ammonia, nitrates, nitrites, dissolved oxygen, pH, salinity, water temperature) in two flow-through (G1, G2) and two RAS (G3, G4) tanks </p>
Models simulating abrupt changes in the Chilika lagoon fishery, the Easter Island community, forest dieback and lake water quality
<p>This deposit is in support of Willcock et al "Earlier collapse of Anthropocene ecosystems driven by multiple faster and noisier drivers". It covers the following items: (i) A list of the files contained within this data deposit; (ii) How to access and download the specialist software required to view and simulate the system dynamics models (STELLA ‘isee Player’); (iii) How to run isee Player to simulate the models; (iv) How to access and download the standard statistical software ‘R’ to run the R scripts; (v) How to load ‘R’ and modify the standard R script to analyse a subset of the model runs. This file will also details the ‘required content’ (e.g. software versions), as specified in the ‘nr-software-policy.pdf’ document.</p> <p>The full descriptions of each of the four system dynamics models used in this manuscript can be read in the following papers:</p> <ol> <li>Lake Chilika – Cooper, G. S. & Dearing, J. A. Modelling future safe and just operating spaces in regional social-ecological systems. <em>Sci. Total Environ.</em> <strong>651</strong>, 2105–2117 (2019), <a href="https://doi.org/10.1016/j.scitotenv.2018.10.118">https://doi.org/10.1016/j.scitotenv.2018.10.118</a></li> <li>Easter Island – Brandt, G. & Merico, A. The slow demise of Easter Island: Insights from a modeling investigation. <em>Front. Ecol. Evol.</em> <strong>3</strong>, 13 (2015), <a href="https://www.frontiersin.org/article/10.3389/fevo.2015.00013">https://www.frontiersin.org/article/10.3389/fevo.2015.00013</a></li> <li>Lake phosphorus – Wang, R. <em>et al.</em> Flickering gives early warning signals of a critical transition to a eutrophic lake state. <em>Nature</em> <strong>492</strong>, 419–22 (2012), <a href="http://dx.doi.org/10.1038/nature11655">http://dx.doi.org/10.1038/nature11655</a></li> <li>TRIFFID - Ritchie, P. D. L., Clarke, J. J., Cox, P. M. & Huntingford, C. Overshooting tipping point thresholds in a changing climate. <em>Nat. 2021 5927855</em> <strong>592</strong>, 517–523 (2021), <a href="http://dx.doi.org/10.1038/nature11655">http://dx.doi.org/10.1038/nature11655</a></li> </ol>
Water Quality Features' Changes - WQeMS Raster Products
<p>This dataset contains samples of the Water Quality Features' Changes service of the WQeMS H2020 project.</p>
Monthly lake water quality data (May-September 2022) following the Greenwood Fire in northeastern Minnesota v1.0
<p>This repository contains lake water quality responses to the 2021 Greenwood Fire in Superior National Forest, Minnesota, USA (near Isabella, MN in northeastern MN). Thirty lakes (15 burned watershed, 15 control) were sampled monthly from May-September 2022 along various fire disturbance gradients (e.g., % watershed burned) and in relation to hydrologic connectivity (i.e., drainage vs. isolated lakes). Much of the non-water quality data we used came from published sources, which are described and referenced below. This repository also contains R code used to analyze and visualize data, as well as some output figures.</p>
Southwest United States Wetland Water Quality and Macroinvertebrate Data 2018-2022
Water quality and macroinvertebrate data were collected between 2018 and 2020 from 14 different wetland and riparian sites spanning across West Texas, New Mexico, and Arizona. Water quality data such as Cl, SO4, and conductivity were collected as well as nutrients such as NO3, PO4, and Total Dissolved Nitrogen. Macroinvertebrate data were collected from all sites during the summer months (June, July, and August).
High-frequency water quality and air parameters from large lake Võrtsjärv, Estonia: 2010-2019
This high frequency water-air dataset was collected from large shallow Lake Võrtsjärv (Estonia) with an automated lake monitoring buoy system and was used in the analyses described in the manuscript by Thayne, M.W., B. Kraemer, J.P. Mesman, A. Laas, E. de Eyto, B. W. Ibelings, R. Adrian. “Trophic state effects on antecedent lake characteristics shape the resistance and resilience of lakes following extreme storms”. Dataset contains every 10-minute measurements from the open water periods in years 2010-2019. Underwater measurements were conducted with Yellow Springs Instrument multiparameter sonde model YSI 6600 V2-4. Underwater measurements contain the collected values of pH, dissolved oxygen, dissolved oxygen saturation, water temperature, specific conductance, water turbidity, chlorophyll concentration (calculated by the sensor from fluorescence values), and the abundance of the bluegreen algae (calculated by the sensor from phycocyanin fluorescence values). Air parameters were collected with the Vaisala multiparameter weather station model WXT520 and contain measurements of wind direction, wind speed, air temperature, atmospheric pressure, and cumulative amount of rain between measurement periods. All air measurements were collected 2 m above from the water surface. Additionally, solar irradiance measurements were collected from the automated buoy system with the Licor pyranometer model LI-200, those measurements contain values in two different columns: average solar irradiance in W/m2 and average photon flux density values in micromoles per square meter per second.
Water quality measurements, stream order, channel slope and hydraulic equations of conterminous USGS sites: 1919-2009.
Streams and rivers emit petagrams of CO2 yet there is little known about how discharge (Q) variability impacts stream CO2 at broad scales. Herein, we compiled historical water quality (including pH, alkalinity and temperature) measurements for conterminous USGS sites and coupled them with daily Q for this analysis (the water_quality.csv dataset, 10,822 sites). Based on this dataset, NHDplus channel slopes (NHDplus_slopeSO.csv, 24,764 sites) and hydraulic geometry equations (lm_vQ.csv, 12,854 sites), we calculated partial pressure of dissolved CO2 (pCO2), gas transfer velocity (k) and CO2 effluxes (F) for a total of 813 USGS sites across conterminous US. We derived hydrologic responses (log-linear regressions) for pCO2, k and F versus Q at each site and explored how these responses varied across stream order and different regions. Ancillary datasets provided coordinates (coor_sites.xls), hydrologic unit code (HUC.csv), and watershed area of conterminous USGS sites (watersheds_area.csv).
Petit-lac-Saint-François surface water quality monitoring data
Water Quality samples were collected at Lake Inlet, Outlet, and In-Lake sites between October 2009 and September 2020. Water Samples were collected on a weekly, same-day-of-the-week basis, between 10 a.m. and noon, year-round. Field sampling was conducted by the same technician during the entire period to ensure method consistency and sampling frequency was maintained throughout, except for the winter of 2017, during which sampling was suspended. Epilimnion samples were collected using a swing sampler with a wide neck, polyethylene bottle (Nasco Sampling, Madison, WI, USA), and composited in an acid-washed, opaque, 4-L polyethylene bottle pre-conditioned with lake water. Four grab samples were taken to account for spatial heterogeneity that can be substantial within distances of a few meters, particularly when surface phytoplankton blooms are present. The grab samples were collected by tilting the swing sampler bottle approximately 45 degrees and allowing it to fill as it was submerged 8 to 15 cm below the surface. During periods of ice cover, access holes were drilled or cut through the ice to collect samples. For dissolved parameters, samples were filtered on the same day as collection. Quality control measures, including field, transport, and laboratory blanks, consisting of HPLC grade water and preservative where required, as well as split samples for interlaboratory comparisons, were included quarterly in the sampling program along with regular samples. These were used to establish practicable detection limits and to monitor for levels of contaminants to which field samples might be exposed.
Water quality, phytoplankton, and zooplankton in the Sacramento Deep Water Ship Channel, CA
Drivers of phytoplankton and zooplankton dynamics vary spatially and temporally in estuaries due to variation in hydrodynamic exchange and residence time, complicating efforts to understand controls on food web productivity. We conducted approximately monthly (2012 – 2019; n = 74) longitudinal sampling at ten fixed stations along a freshwater tidal terminal channel in the San Francisco Estuary, California, characterized by seaward to landward gradients in water residence time, turbidity, nutrient concentrations, and plankton community composition. We used multivariate autoregressive state space (MARSS) models to quantify environmental (abiotic) and biotic controls on phytoplankton and mesozooplankton biomass. The importance of specific abiotic drivers (e.g. water temperature, turbidity, nutrients) and trophic interactions differed significantly among hydrodynamic exchange zones with different mean residence times. Abiotic drivers explained more variation in phytoplankton and zooplankton dynamics than a model including only trophic interactions, but individual phytoplankton-zooplankton interactions explained more variation than individual abiotic drivers. Interactions between zooplankton and phytoplankton were strongest in landward reaches with the longest residence times and the highest zooplankton biomass. Interactions between cryptophytes and both copepods and cladocerans were stronger than interactions between bacillariophytes (diatoms) and zooplankton taxa, despite contributing less biovolume in all but the most landward reaches. Our results demonstrate that trophic interactions and their relative strengths vary in a hydrodynamic context, contributing to food web heterogeneity within estuaries at spatial scales smaller than the freshwater to marine transition.
Spatial Survey of Water Quality in Lake Arrowhead, TX, USA
A rapid spatial survey of surface water was conducted in in Lake Arrowhead, Texas, USA on 2022 Aug 12. A sensor-equipped boat (Whaler Montawk 210) covered 62.3 km in 180 minutes, prioritizing water overlying the main river channel and navigable sections of reservoir arms. The mean boat speed over the entire survey was 21 km/hr, but in deeper water speeds of 30 to 55 km/hr were common. With this method, a pump brings surface lake water through a transom-mounted intake pipe onto the boat deck in a continuous flow-through system that contains a YSI Exo 2 sonde, flow cell, and probes for turbidity, specific conductivity, pH, and water temperature. A Garmin GPS 18X LVC was used to log latitude, longitude, and boat speed. All sensor and GPS data were logged in the field at 1 s intervals.
Caloosahatchee River Estuary Optical Water Quality Data (May 2008 - May 2020)
This dataset is an aggregated dataset from various sources including the South Florida Water Management District and Lee County (Florida) Environmental Lab and includes parameters of optical water quality. Optical water quality samples were collected throughout the Caloosahatchee River Estuary from the head of the estuary to its outlet in San Carlos Bay and the Gulf of Mexico. Parameters within the dataset include light attenuation coefficient, Secchi disk depth, chlorophyll-a concentration, turbidity, total suspended solid concentration, color, water temperature, specific conductivity, and salinity. Samples were collected from various agencies from May 2008 to May 2020. Other water quality parameters were also collected and some of the monitoring continued to present but is not presented here.
Data used in the Final Draft Scientific Basis Report Supplement in Support of Proposed Voluntary Agreements for the Sacramento River, Delta, and Tributaries Update to the San Francisco Bay/Sacramento-San Joaquin Delta Water Quality Control Plan
This dataset includes modeled data describing the potential benefits of the Voluntary Agreements (VAs) from the Final Draft Scientific Basis Report Supplement in Support of Proposed Voluntary Agreements for the Sacramento River, Delta, and Tributaries Update to the San Francisco Bay/Sacramento-San Joaquin Delta Water Quality Control Plan.
FISHPASS ASSESSMENT PLAN LONG-TERM MONITORING OF HYDROLOGIC AND WATER QUALITY DATA
The Great Lakes Fishery Commissions’ (GLFC) FishPass project seeks to reconnect the waterscape for only desired species (i.e., selective passage) by integrating a multitude of existing and novel passage techniques and technologies. The probability of a fish passing through a sorting system is dependent on environmental conditions and a fish’s motivation ─ its internal state in relation to environmental stimuli. While fish decision making abilities introduce complexity to the sorting operations, they also provide an opportunity to exploit behavioral tendencies and abilities to achieve selective sorting. The FishPass Assessment Plan details a monitoring program aimed at quantifying fish movement and sorting capabilities associated with both individual mechanisms and integrated sorting systems. The results of the monitoring program will be used to inform future adjustments to the selection of techniques and technologies and their configuration to optimize passage of desirable species while blocking and/or removing undesirable species. A key component to the Assessment Plan is the long-term monitoring of abiotic variables in and around FishPass. This data set contains the hydrologic (e.g., river discharge, water level) and water quality data (e.g., temperature, specific conductivity, conductivity, and turbidity) collected at mostly static stations throughout the Boardman/Ottaway River. The dataset is updated annually. These data are collected until the initiation and/or substantial completion of the FishPass structure. Collection of this type of data are expected to continue after FishPass construction completion but modifications to the extent and location of monitoring stations are anticipated. As a result, a new dataset will be updated in the future containing all long term hydrologic and water quality monitoring post construction. R. Swanson, GLFC Assessment Biologist, is primarily responsible for maintaining the monitoring equipment, data retrieval, quality assuran
Water quality and stage in Gibson Jack Creek, SE Idaho, March-October 2020
Diel dissolved organic matter (DOM) variation can be used to understand hydrological and biogeochemical controls on organic matter cycling. We collected high-frequency fluorescent DOM data, and additional high-frequency data that could be used to parse controls, including stage, specific conductivity, water and air temperature, dissolved oxygen, and light availability at three locations in a non-perennial reach in Gibson Jack Creek, in southeastern Idaho. Weekly grab samples were collected for water chemistry throughout the study period. Data were collected from March 2020 through October 2020.
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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.