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19,393 results for “water”
Monthly aggregated Water Vapor MODIS MCD19A2 (1 km): Monthly time-series (2006-2008)
<p>This data is part of the <em>Monthly aggregated Water Vapor MODIS MCD19A2 (1 km)</em> dataset. Check the related identifiers section on the Zenodo side panel to access other parts of the dataset.</p><p><strong>General Description</strong></p><p>The monthly aggregated water vapor dataset is derived from <a href="https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MCD19A2"><abbr title="MCD19A2 MODIS/Terra+Aqua daily product">MCD19A2 v061</abbr></a>. The Water Vapor data measures the column above ground retrieved from MODIS near-IR bands at 0.94μm. The dataset time spans from 2000 to 2022 and provides data that covers the entire globe. The dataset can be used in many applications like water cycle modeling, vegetation mapping, and soil mapping. This dataset includes:</p><ul><li><strong>Monthly time-series:</strong><br>Derived from <em>MCD19A2 v061</em>, this data provides a monthly aggregated mean and standard deviation of daily water vapor time-series data from 2000 to 2022. Only positive non-cloudy pixels were considered valid observations to derive the mean and the standard deviation. The remaining no-data values were filled using the <abbr title="Moving Window Median">TMWM</abbr> algorithm. This dataset also includes smoothed mean and standard deviation values using the Whittaker method. The quality assessment layers and the number of valid observations for each month can provide an indication of the reliability of the monthly mean and standard deviation values.</li><li><strong>Yearly time-series:</strong><br>Derived from <em>monthly time-series</em>, this data provides a yearly time-series aggregated statistics of the monthly time-series data.</li><li><strong>Long-term data (2000-2022):</strong><br>Derived from <em>monthly time-series</em>, this data provides long-term aggregated statistics for the whole series of monthly observations.</li></ul><p><strong>Data Details</strong></p><ul><li><strong>Time period:</strong> 2006–2008</li><li><strong>Type of data:</strong> Water vapor column above the ground (0.001cm)</li><li><strong>How the data was collected or derived:</strong> Derived from MCD19A2 v061 using <a href="https://earthengine.google.com">Google Earth Engine</a>. Cloudy pixels were removed and only positive values of water vapor were considered to compute the statistics. The time-series gap-filling and time-series smoothing were computed using the <a href="https://github.com/scikit-map/scikit-map">Scikit-map</a> Python package.</li><li><strong>Statistical methods used:</strong> Four statistics were derived: mean, standard deviation, smoothed mean, smoothed standard deviation.</li><li><strong>Limitations or exclusions in the data:</strong> The dataset does not include data for Antarctica.</li><li><strong>Coordinate reference system:</strong> EPSG:4326</li><li><strong>Bounding box (Xmin, Ymin, Xmax, Ymax):</strong> (-180.00000, -62.00081, 179.99994, 87.37000)</li><li><strong>Spatial resolution:</strong> 1/120 d.d. = 0.008333333 (1km)</li><li><strong>Image size:</strong> 43,200 x 17,924</li><li><strong>File format:</strong> Cloud Optimized Geotiff (COG) format.</li></ul><p><strong>Support</strong></p><p>If you discover a bug, artifact, or inconsistency, or if you have a question please use some of the following channels:</p><ul><li>Technical issues and questions about the code: <a href="https://gitlab.com/openlandmap/global-layers/-/issues">GitLab Issues</a></li><li>General questions and comments: <a href="https://disqus.com/home/forums/landgis">LandGIS Forum</a></li></ul><p><strong>Name convention</strong></p><p>To ensure consistency and ease of use across and within the projects, we follow the standard Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describes important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are:</p><ol><li>generic variable name: wv = Water vapor</li><li>variable procedure combination: mcd19a2v061.seasconv = MCD19A2 v061 with gap-filling algorithm</li><li>Position in the probability distribution / variable type: m = mean | sd = standard deviation | n = number of observations | qa = quality assessment</li><li>Spatial support: 1km</li><li>Depth reference: s = surface</li><li>Time reference begin time: 20060101 = 2006-01-01</li><li>Time reference end time: 20081231 = 2008-12-31</li><li>Bounding box: go = global (without Antarctica)</li><li>EPSG code: epsg.4326 = EPSG:4326</li><li>Version code: v20230619 = 2023-06-19 (creation date)</li></ol>
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>
Time Series of Water Levels in a Coastal Barrier-Lagoon System, NW Spain (2009-2012)
<p>This repository contains the data recorded by water-level loggers (survey-pressure transducers) deployed in a barrier-lagoon coastal system, which were used in the study by</p> <p><strong>R. González-Villanueva, M. Pérez-Arlucea, and S. Costas titled 'Lagoon Water-Level Oscillations Driven by Rainfall and Wave Climate,' published in Coastal Engineering, Volume 130, 2017, Pages 34-45, ISSN 0378-3839, available at <a href="https://doi.org/10.1016/j.coastaleng.2017.09.013">https://doi.org/10.1016/j.coastaleng.2017.09.013</a></strong></p> <p>The repository consists of three text files:</p> <ol> <li><strong>lagoon_water_level.txt</strong></li> <li><strong>sea_level.txt</strong></li> <li><strong>phreatic_level.txt</strong></li> </ol> <p>Each file includes a header with metadata and information for each column in the data file, as follows:</p> <ul> <li><strong>pt_id</strong>: ID of the individual record</li> <li><strong>pt:</strong> instrument used</li> <li><strong>lat</strong>: Latitude in WGS84</li> <li><strong>long</strong>: Longitude in WGS84</li> <li><strong>units</strong>: Indicates the measurement unit for the water level recordings</li> <li><strong>temporal resolution</strong>: Indicates the time interval between two consecutive measurements</li> <li><strong>column 1</strong>: Description of the data contained in column 1</li> <li><strong>column 2</strong>: Description of the data contained in column 2</li> <li><strong>column n</strong>: Description of the data contained in column n</li> </ul>
Evaluation of a wind tunnel designed to investigate the response of evaporation to changes in the incoming longwave radiation at a water surface
<p>Experimental Record of a Longwave-Evaporation experiment. The record to be referenced in a forthcoming scientific paper.</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
Water chemistry and aquatic vegetation data from Les Cheneaux Islands, Northern Lake Huron, Michigan, USA, 2016-2018
Remote sensing approaches that could identify species of submerged aquatic vegetation (SAV) and measure their extent in lake littoral zones would greatly enhance their study and management, especially if they can provide faster or more accurate results than traditional field methods. Remote sensing with multispectral sensors can provide this capability, but SAV identification with this technology must address the challenges of light extinction in aquatic environments where chlorophyll, dissolved organic carbon, and suspended minerals can affect water clarity and the strength of the sensed light signal. Here, we present environmental data collected to support a study using an unmanned aerial system (UAS)-enabled methodology to identify the extent of the invasive SAV species Myriophyllum spicatum (Eurasian watermilfoil, or EWM) in the Les Cheneaux Islands area of northwestern Lake Huron, Michigan, USA. Data collected includes water chemistry (nitrogen, phosphorus, carbon, suspended solids, chlorophyll a), light profiles, and submerged aquatic vegetation characteristics including cover, species dominance using aquatic vegetation survey methods (AVAS), and biomass.
Spatiotemporal variation in internal phosphorus loading, sediment characteristics, water column chemistry, and thermal mixing in a hypereutrophic reservoir in southwest Iowa, USA (2019-2020)
The primary aim of the data product is to quantify seasonal and spatial variation in sediment phosphorus fluxes in a temperate reservoir and evaluate mechanisms responsible for instances of elevated sediment phosphorus release. We studied Green Valley Lake, a hypereutrophic reservoir in southwest Iowa, USA, from 2019 to 2020. We measured sediment phosphorus flux rates and potential explanatory variables at three sites along the longitudinal gradient of the reservoir over six sampling events during winter and summer stratification as well as mixing events in the spring, summer, and fall. Ex situ sediment core incubations were used to measure sediment P release rates under ambient temperature and dissolved oxygen conditions. Explanatory variables measured included sediment phosphorus chemistry, sediment physical characteristics, epilimnetic and hypolimnetic nutrient concentrations, and thermal stratification patterns. These data will be used to identify mechanisms driving hot spots and hot moments of sediment phosphorus release, which will contribute to our understanding of how areas of lakebed and times of the year can disproportionately influence whole-lake water chemistry.
Water chemistry data from synoptic sampling of 235 Lake Michigan tributaries: 10-15 July, 2018
This dataset includes nutrient (total nitrogen and phosphorus, soluble reactive phosphorus, and dissolved inorganic nitrogen [nitrate+nitrite+ammonium]) and chloride concentrations for 235 tributaries of Lake Michigan collected during a synoptic sampling event from 10-15 July, 2018. The dataset also includes modeled discharge metrics for the 235 sampled watersheds, as well as spatial watershed characteristics.
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.
Water soluble organic matter from Delmarva Bay soils
Little is known about how hydrologic processes along the terrestrial-aquatic interface in wetland dominated landscapes influence carbon dynamics, particularly regarding soil-derived dissolved organic matter (DOM) transport and transformation. To understand the role of different soil horizons as potential sources of DOM to wetland systems, we measured water soluble organic matter (WSOM) in soil horizons collected from upland to wetland transects at four Delmarva Bay wetlands. The Delmarva Bays used in this study are located on property managed by The Nature Conservancy on the Delmarva Peninsula in the eastern United States. Transects ranged from 25 – 45 m in length beginning from a monitoring well in the wetland center to an upland monitoring well. Each transect had four points (Upland, Transition, Edge, and Wetland). Soils were sampled in the late winter (January 17 and March 10) and autumn (September 21 and November 1) of 2020. Soils were sampled by horizon to a depth of approximately 50 cm at each transect point. WSOM extracted in the laboratory was analyzed for WSOM concentration, reported as Water Soluble Organic Carbon (mg WSOC / g soil). WSOM absorbance and fluorescence data were used to calculate composition metrics, providing insight to organic matter sources and chemical characteristics. WSOM fluorescence excitation-emission matrices were evaluated using the 13 component Cory and McKnight (2005) PARAFAC model. Extracted leaf litter, surface water, and groundwater samples were collected in addition to soil samples for the purpose of comparing WSOM to DOM end-members along the Delmarva Bay terrestrial-aquatic continuum. Continuous water level data, averaged to a daily time-step, was collected over the 2020 water year (October 1, 2019 to September 30, 2020) in previously established wetland and upland monitoring wells. The hydrologic conditions (e.g. mean water level, number of saturation events, duration of saturation) at each transect point were characterize
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
Marcell Experimental Forest chemistry of surface water draining the S6 catchment, 1986 - ongoing
This data set is a record since 1986 of chemistry for surface water draining the S6 catchment at the Marcell Experimental Forest (MEF) in Itasca County, Minnesota. Unfiltered water is usually collected every one or two weeks as part of the long-term monitoring program of the S6 catchment. Some samples were collected more often for various other studies and are included in this data set. Samples are routinely measured for pH, specific conductivity, anions (chloride, sulfate), cations (calcium, magnesium, potassium, sodium, aluminum, iron, manganese, strontium), silicon, nutrients (ammonium, nitrate+nitrite, soluble reactive phosphorus, total nitrogen, total phosphorus), and total organic carbon. Occasionally, stable water isotopes as well as concentrations of dissolved organic carbon (DOC), bacterial respiration of dissolved organic matter, biodegradable DOC (BDOC), ferrous and ferric iron, total mercury (filtered or unfiltered), and methylmercury (filtered or unfiltered) were measured. Ultraviolet (UV) absorbance, a measure of water color or dissolved organic matter optical properties, was also measured for some samples. More solutes and values will be added as additional metadata are documented (pre-1986 to 1992), water samples are collected and analyzed (concentrations and isotopes), or archived water samples are analyzed for stable water isotopes. The MEF is operated and maintained by the USDA Forest Service, Northern Research Station.
Summer water chemistry, phytoplankton and zooplankton community composition, size structure, and biomass in a shallow, hypereutrophic reservoir in southwestern Iowa, USA (2019).
This data product contains data for Green Valley Lake, a hypereutrophic reservoir in southwest Iowa (USA) from the summer of 2019. We sampled and quantified zooplankton, phytoplankton, and nutrient concentrations (total N, total P, soluble reactive P, nitrate) in the lake weekly with the primary aim of assessing consumer nutrient cycling, specifically zooplankton nutrient cycling, in a hypereutrophic reservoir. Weekly plankton sampling included quantifying zooplankton and phytoplankton biomass, community composition, and size structure. Phytoplankton size was measured as the greatest axial linear distance which would be approached by a zooplankton grazer. Allometric equations from the literature were applied to the zooplankton size measurements to estimate zooplankton community excretion of N and P. We found that the estimated contribution of zooplankton excretion to the dissolved P pool was substantial in the spring. Further, we found evidence that zooplankton affected phytoplankton size distributions through selective grazing of smaller phytoplankton cells likely affecting nutrient uptake and storage by phytoplankton.
Data from “A Mixed Method Approach to Understanding the Public Health Impact of a School-Based Citizen Science Program to Reduce Arsenic in Private Well Water”
Objectives We have approached the problem of low well water testing rates in Maine and New Hampshire communities by developing the All About Arsenic (AAA) project, which engages secondary school teachers and students as citizen scientists in collecting well water samples for analysis of arsenic and other toxic metals and supports their outreach efforts to their communities. Methods We assessed this project’s public health impact by analyzing student data relative to existing well water quality datasets in both states. In addition, we surveyed private well owners who contributed well water samples to the project to determine the actions taken to mitigate arsenic in well water. Data The data presented here are used in the analyses performed for the publication: "A Mixed Method Approach to Understanding the Public Health Impact of a School-Based Citizen Science Program to Reduce Arsenic in Private Well Water.” Additional data may be available at: The Anecdata Project Page: https://anecdata.org/projects/view/299 The project website: https://www.allaboutarsenic.org/
Hourly water chemistry measurements at the mouth of West Falmouth Harbor, MA, USA from 2005 to 2019 and 2023
West Falmouth Harbor (West Falmouth, MA, USA) has been experiencing a dramatic increase in nitrogen loading from an upgradient municipal wastewater treatment facility since the early 2000s. As part of a long-term study into the effects of this nitrogen enrichment, we have been measuring water chemistry at the mouth of the harbor to calculate exchange between the harbor and adjacent coastal waters of Buzzards Bay. Water samples were taken hourly over 24- to 48-hour periods during several periods in 2005-2009, 2014, 2017, 2019, and 2023. Data from 2005-2009 were collected year-round; samples from 2014 and later were collected during June through August. Samples were processed for ammonium, phosphate, nitrate + nitrite, total nitrogen, and total phosphorus unless otherwise notated. During some sampling years, additional samples were run for silicate, chlorophyll, total dissolved nitrogen, total dissolved phosphorus, dissolved organic carbon, particulate organic carbon, and particulate organic nitrogen. Salinity is reported for all samples. Samples were collected with an ISCO autosampler and stored on ice until analysis. Full analysis details and quality control methods are available in Hayn et al. 2014 (doi: 10.1007/s12237-013-9699-8) and Hayn 2025 (doi: 10.7298/btm6-ba76).
Time series of high-frequency sensors measuring water temperature and dissolved oxygen at discrete depths in Falling Creek Reservoir, Virginia, USA in 2012-2018
We measured water temperature and dissolved oxygen at multiple depths in Falling Creek Reservoir (Vinton, Virginia, USA) with high-frequency (10 to 15-minute) sensors for different durations during 2012 to 2018. Falling Creek Reservoir is owned and managed by the Western Virginia Water Authority as a primary drinking water source for Roanoke, Virginia. All measurements were collected at discrete depths at the deepest site of the reservoir adjacent to the dam. The sensors consisted of: 1) InsiteIG dissolved oxygen and water temperature sensors (Model 20 dissolved oxygen sensor) at both 1 m (November 2015 - December 2018) and 8 m (September 2012 - December 2018) and 2) HOBO (HOBO Pendant Temperature/Light 64K Data Logger) water temperature loggers deployed at 1, 2, 3, 4, 5, 6, 7, 8, and 9.3 m depths (September 2015 - January 2018).
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.
Lake Tahoe Nutrients data for discrete water samples
Lake water nutrient data measured on discrete water samples from Lake Tahoe, CA/NV. There are two sampling stations Index (LTP, 39.0972 -120.155) and Mid-lake (MLTP, 39.1417 -120.0153). See methods for details
ScienceDex guides
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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.