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484 results for “water quality”
LBA-ECO LC-07 Water Quality, CO2, Chlorophyll, Lago Curuai, Para, Brazil: 2003-2004
This data set reports (1) concentrations of total, organic, and inorganic suspended solids; dissolved inorganic, and organic carbon; chlorophyll-a and (2) measurements of turbidity, ph, temperature, transparency, conductivity, and calculated carbon dioxide (CO2) in water samples collected from Lago Curuai (Lake Curuai), in the floodplain of the Amazon River south of Obidos, Para, Brazil. Approximately 70 stations were sampled during four phases of the hydrological cycle: receding (September 2003), low (November 2003), rising (February 2004), and high water (June 2004). There is one comma-delimited data file with this data set.
Delta-X: In Situ Water Quality Indicators across MRD, LA, USA, 2021, Version 2
This dataset provides in situ measurements of water temperature (degrees C), salinity (PSU), turbidity (FNU), and chlorophyll-a fluorescence (RFU) in surface of the Atchafalaya River and Terrebonne Basins during the Spring (2021-03-25 to 2021-04-22) and Fall (2021-08-14 to 2021-09-24) field efforts by the Delta-X project. Field sampling was paused on August 25 and resumed on September 13, 2021, due to the landfall of Hurricane Ida on 2021-08-26 approximately 70 km east of the study site. Water quality changes caused by the hurricane were expected to be minimal. Measurements were collected in multiple channels of varying width (from a few meters to >100 m), near Delta-X intensive study sites, in open bays and lakes, and at a few locations in the nearshore Gulf of Mexico using either a YSI ProDSS water quality probe or a YSI EXO3 water quality probe.
Delta-X: AVIRIS-NG L3-derived Water Quality, TSS, and Turbidity, MRD, V3
This dataset includes estimates of total suspended solids (TSS) concentration and turbidity for waters of the Atchafalaya River and Terrebonne Basins of the Mississippi River Delta (MRD) in coastal Louisiana. Estimates were derived from Level 2 (L2) BRDF-corrected imagery from NASA's Next Generation Airborne Visible Infrared Imaging Spectrometer (AVIRIS-NG). AVIRIS-NG imagery was collected from March 27-April 6 (spring) and August 20-25 (fall), 2021, as part of the 2021 Delta-X campaign. Algorithms for TSS and turbidity estimation were developed using in-situ remote-sensing reflectance measured at field sampling stations paired with in-situ measures of turbidity from a water quality probe and TSS from water samples. Using the in-situ data, a partial least squares regression (PLSR) model was developed for each AVIRIS-NG wavelength. A subset of the in-situ data, collected during relatively clear AVIRIS-NG overflights, was held out to validate the PLSR model. The PLSR algorithm was then applied to AVIRIS-NG imagery to retrieve TSS and turbidity across the study area. The measurement units for TSS and turbidity estimates are mg L-1 and Formazin Nephelometric Units (FNU), respectively, and the spatial resolution is 3.8 to 5.4 m as determined by the AVIRIS-NG imagery. The dataset includes binary cloud and water masks. These data quantify the mesoscale (i.e., on the order of 1 ha) patterns of soil accretion that control land loss and gain and predict the resilience of deltaic floodplains under projected relative sea-level rise. Gridded estimates are provided in netCDF format, and regression coefficients are included in a comma-separated values (CSV) file. This is Version 3 of this dataset. All previously released data were updated to the latest available versions.
Water Quality and Spectral Reflectance, Peace-Athabasca Delta, Canada, 2010-2011
The Peace-Athabasca Delta (PAD) is a hydrologically complex and ecologically diverse freshwater delta formed by the confluence of the Peace, Athabasca, and Birch Rivers near the western end of Lake Athabasca. This data set includes 3 comma-delimited ASCII files: one containing water quality data and site characteristics from June and July 2010, a second containing water quality data and site characteristics for June and July 2011, and a third containing spectral reflectance of the water surface for 2011. The 2010 data file has measurements from 62 unique sites, the majority of which were revisited in 2011. Both of the 2011 data files have measurements from 99 unique sites visited 1-4 times.
Data from: Assessment of grain quality in terms of functional group response to elevated [CO2], water and nitrogen using a meta-analysis: Grain protein, zinc and iron under future climate
The increasing [CO2] in the atmosphere increases crop productivity. However, grain quality of cereals and pulses are substantially decreased and consequently compromise human health. Meta-analysis techniques were employed to investigate the effect of elevated [CO2] (e[CO2]) on protein, zinc (Zn) and iron (Fe) concentrations of major food crops (542 experimental observations from 135 studies) including wheat, rice, soybean, field peas and corn considering different levels of water and nitrogen (N). Each crop, except soybean, had decreased protein, Zn and Fe concentrations when grown at e[CO2] concentration ( ≥550 μmol mol-1) compared ambient [CO2] (a[CO2]) concentration (≤ 380 μmol mol-1). Grain protein, Zn and Fe concentrations were reduced under e[CO2], however, the responses of protein, Zn and Fe concentrations to e[CO2 ] were modified by water stress and N. There was an increase in Fe concentration in soybean under medium N and wet conditions but non-significant. The reductions in protein concentrations for wheat and rice were ~ 5-10%, and the reductions in Zn and Fe concentrations were ~ 3-12%. For soybean, there was a small and non-significant increase of 0.37% in its protein concentration under medium N and dry water, while Zn and Fe concentrations were reduced by ~ 2-5%. The protein concentration of field peas decreased by 1.7%, and the reductions in Zn and Fe concentrations were ~ 4-10%. The reductions in protein, Zn and Fe concentrations of corn were ~ 5-10%. Bias in the dataset was assessed using a regression test and rank correlation. The analysis indicated that there are medium levels of bias within published meta-analysis studies of crops responses to Free Air [CO2]Enrichment (FACE). However, the integration of the influence of reporting bias did not affect the significance or the direction of the [CO2] effects.
Data from: Long-term agroecosystem research in the Central Mississippi River Basin: Goodwater Creek Experimental Watershed and regional herbicide water quality data
PLEASE NOTE, THESE DATA ARE ALSO REFERRED TO IN ANOTHER PUBLICATION. PLEASE SEE http://doi.org/10.2134/jeq2013.12.0518. Goodwater Creek Experimental Watershed (GCEW) has been the focus area of a long-term effort to document the extent of and to understand the factors controlling herbicide transport. We document the datasets generated in the 20-yr-long research effort to study the transport of herbicides to surface and groundwater in the GCEW. This long-term effort was augmented with a spatially broad effort within the Central Mississippi River Basin encompassing 12 related claypan watersheds in the Salt River Basin, two cave streams on the fringe of the Central Claypan Areas in the Bonne Femme watershed, and 95 streams in northern Missouri and southern Iowa. Details of the analytical methods, periods of record, number of samples, study locations, and means of accessing these data are provided. In addition, a brief overview of significant findings is presented. A key finding was that near-surface restrictive soil layers, such as argillic horizons of smectitic mineralogy, result in greater herbicide transport than soils with high percolation and low clay content. Because of this, streams in the claypan soil watersheds of northeastern Missouri have exceptionally high herbicide concentrations and relative loads compared with other areas of the Corn Belt.
Water Quality Data for Narragansett Bay, RI (USA) from 2014 to 2022
<p>This dataset includes results of a monthly monitoring program conducted in Narragansett Bay, RI (USA)<br>between January 2014 and December 2022. Eight stations were sampled at three depths (surface, mid-depth,<br>and bottom) using a combination of sondes, secchi disk, and discrete water collections. Water<br>samples were processed in laboratory immediately after collection to be either filtered, preserved, or<br>stored and then later analyzed for chlorophyll-a, dissolved inorganic nutrients (nitrate+nitrite, nitrite,<br>ammonium, and orthophosphate), dissolved organic carbon, stable isotopes of particulate carbon and<br>nitrogen, and total suspended solids. These water quality data are being made available to use, in<br>conjunction with pre-existing datasets collected by others, to better understand the ecological dynamics<br>of the Narragansett Bay ecosystem.</p>
Laboratory water quality monitoring data from full scale CS#3 DWDN for the DBP prediction model
<p>Lab measurements of water quality based on manual sampling including ordinary monitoring and special monitoring performed in SafeCREW project.</p> <p>Laboratory LIMS database.</p> <p>Provide water quality measurements based on the planned monitoring schedule. Schedule tailored to SafeCREW project needs plus usual legal water sampling.</p>
Lake water quality monitoring data from 8287 northern lakes
<p>This dataset contains water quality monitoring data and lake morphometry data from 8287 lakes collected between 1960 and 2022 in Finland, Sweden, Norway, Canada and the United States (Alaska). Data was sourced from governmental databases and non-profit organizations via data portals and data requests (see Metadata). The dataset contains over 2.6 million standardized and quality-controlled observations of dissolved oxygen, water temperature, total nitrogen, total phosphorus, water colour and ammonia, as well as sampling location, sampling date, sampling depth and key lake properties including lake altitude, surface area, mean depth and maximum depth. We excluded lakes undergoing physical or chemical treatments against hypoxia, lakes in which experiments have been conducted (e.g. nutrient addition). and reservoirs.</p> <p>The consumer of these data ("Data User" herein) should realize that misinterpretation of data may occur if used out of context of the original study. While substantial efforts are made to ensure the accuracy of data and associated documentation, complete accuracy of data sets cannot be guaranteed. All data are made available "as is". The Data User should be aware, however, that data are updated periodically and it is the responsibility of the Data User to check for new versions of the data. The data authors, original data providers and the repository where these data were obtained shall not be liable for damages resulting from any use or misinterpretation of the data. The data user may not create derivatives of this dataset or re-distribute these data to a third party.</p> <p><strong>Note: </strong>if you would like to use this data in your own study, you must contact the author (joachim.jansen@helsinki.fi) to ensure compliance with requirements of the contributors to this synthesis dataset, </p>
Figure 1 from: Kelly-Quinn M, Bruen M, Carlsson J, Gurnell A, Jarvie H, Piggott J (2019) Managing the small stream network for improved water quality, biodiversity and ecosystem services protection (SSNet). Research Ideas and Outcomes 5: e33400. https://doi.org/10.3897/rio.5.e33400
Figure 1 Strahler stream order.
Figure 2 in Macroinvertebrate-based biotic indices for evaluating the water quality of Kargı Stream (Antalya, Turkey)
Figure 2. The number of individuals collected seasonally.
Figure 1 in Water quality assessment in an irrigation pond based on adult caddisfly (Insecta: Trichoptera) assemblages
Figure 1. Sampling site for adult Trichoptera and water quality variables.
Figure 1 from: Rasoloariniaina JR, Ganzhorn JU, Riemann JC, Raminosoa N (2016) Water quality and biotic interaction of two cavefish species: Typhleotris madagascariensis Petit, 1933 and Typhleotris mararybe Sparks & Chakrabarty, 2012, in the Mahafaly Plateau groundwater system, Madagascar. Subterranean Biology 18: 1-16. https://doi.org/10.3897/subtbiol.18.8321
Figure 1 - Study area and survey sites for Typhleotris spp.
Effect of Heated Water-Based Versus Land-Based Exercise Training on Hemodynamic Variables, Functional Capacity and Quality of Life in Older Hypertensive
ClinicalTrials.gov study NCT07131748. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Effects of Warm Water Footbath Intervention on Sleep Quality , Fatigue and Heart Rate Variability in Patients With Heart Failure
ClinicalTrials.gov study NCT06287996. IPD Sharing: NO. Countries: 1. Publications: 0.
STUDY OF GLUCOSE IN DIALYSIS WATER WITH REGARD TO BLOOD PRESSURE AND QUALITY OF LIFE
ClinicalTrials.gov study NCT00278057. IPD Sharing: Not stated. Countries: 1. Publications: 0.
The Effect of Salt Water Nebulization on Cough, Sputum and Quality of Life in Chronic Obstructive Pulmonary Patients
ClinicalTrials.gov study NCT06519188. IPD Sharing: NO. Countries: 1. Publications: 0.
The Effect of Hydrogen-rich Water on Premenstrual Symptoms and Quality of Life
ClinicalTrials.gov study NCT05556252. IPD Sharing: NO. Countries: 1. Publications: 0.
Effect of Early Postoperative Drinking Water on Postoperative Recovery Quality of Patients With Thyroid Surgery
ClinicalTrials.gov study NCT05532384. IPD Sharing: NO. Countries: 1. Publications: 0.
Evaluating a Water Quality Assurance Fund Intervention in Ghana and Kenya
ClinicalTrials.gov study NCT06570005. IPD Sharing: YES. Countries: 2. Publications: 0.
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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)
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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.