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openCC (other)Apr 2022View details →

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.

openCC (other)Sep 2023View details →

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.

openCC (other)Aug 2020View details →

High-frequency water quality data for water temperature, dissolved oxygen, specific conductivity, pH, phycocyanin fluorescence and chlorophyll a fluorescence at Lake Lillinonah, Connecticut, USA, 2011-2017.

From 2011 to 2017, an instrumented buoy maintained by Friends of the Lake (FOTL, friendsofthelake.org) and Fairfield University was deployed on Lake Lillinonah (Connecticut, USA) during the summer months to collect high-frequency water quality data. The buoy was deployed early each summer and remained in the lake until late October. The instrumented buoy was equipped with a YSI 6600 sonde at a depth of 1 meter. The YSI 6600 collected water temperature, dissolved oxygen, specific conductivity, pH, chlorophyll a fluorescence and phycocyanin fluorescence data. Additionally, the instrumented buoy is equipped with an In-Situ RDO sensor which collects water temperature and dissolved oxygen readings at a depth of 15 meters. Included in this data package are datasets containing 15-minute data as well as daily averages from all sensors. Following the summer of 2017, the YSI 6600 sonde was replaced with a YSI EXO2 sonde which collected data on the same variables. Data from the YSIEXO2 sonde, as well as data from the In-Situ RDO sensor during the same period, are available in the EDI data package EDI560. Additionally, the instrumented buoy at Lake Lillinonah is equipped with a water temperature thermistor chain . These data can be found in data packages EDI557 (2011-2015) and EDI558 (2018-current).

openCC (other)Aug 2020View details →

High-frequency water quality data for water temperature, dissolved oxygen, specific conductivity, pH, phycocyanin fluorescence and chlorophyll a fluorescence at Lake Lillinonah, Connecticut, USA, 2018-current.

Since 2011, an instrumented buoy maintained by Friends of the Lake (FOTL, friendsofthelake.org) and Fairfield University has been deployed on Lake Lillinonah (Connecticut, USA) during the summer months to collect high-frequency water quality data. The buoy is deployed early each summer and remains in the lake until late October. Since 2018, the instrumented buoy has been equipped with a YSI EXO2 sonde at a depth of 1 meter. The YSI EXO2 collects water temperature, dissolved oxygen, specific conductivity, pH, chlorophyll a fluorescence and phycocyanin fluorescence data. Additionally, the instrumented buoy is equipped with an In-Situ RDO sensor which collects water temperature and dissolved oxygen readings at a depth of 15 meters. Included in this data package are datasets containing 15-minute data as well as daily averages from both sensors from 2018 to present. Prior to 2018, the instrumented buoy was equipped with a YSI 6600 sonde, which collected data on the same variables (2011-2017). Data from the YSI 6600 sonde, as well as data from the In-Situ RDO sensor during the same period, are available in the EDI data package EDI559. Additionally, the instrumented buoy at Lake Lillinonah is equipped with a water temperature thermistor chain sensor. These data can be found in data packages EDI557 (2011-2015) and EDI558 (2018-current).

openCC (other)Sep 2020View details →

Water quality data collected by the Citizen-Led Environmental Observatory (CLEO) from multiple nearshore sites in Lake Lillinonah, Connecticut, USA, 2010-current

Included in this data package are water quality data from the Citizen-Led Environmental, a Observatory (CLEO) volunteer water quality monitoring program run by Friends of the Lake (FOTL) and Fairfield University at Lake Lillinonah, Connecticut, USA. The program has been operational since 2008 (data available 2010-current). Trained volunteer monitors collect data from dock locations across the lake on water temperature, Secchi disk depth, water color, presence of floating woody debris, recreation potential, trash, particle type and surface scum. Volunteers collect data between 3:00 and 7:00 PM three times per week from Memorial Day through Labor Day. In addition to the variables listed above, CLEO volunteers collect routine water samples on a biweekly basis, as well as any time there is a notable algal bloom. The routine samples are analyzed for nutrient (total nitrogen and total phosphorus) concentrations as well as concentrations of the cyanobacterial toxin microcystin. The blooms samples are analyzed for microcystin only. These data are available in EDI packages EDI568 (nutrients) and EDI569 (toxins).

openCC0May 2017View details →

LAGOS-NE-GIS v1.0: 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: 2013-1925

This data package, LAGOS-NE-GIS v1.0, 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-NE-GEO 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 GIS v1.0 module includes GIS datasets for: lake polygons and their hydrologic classification; wetland polygons and their classification; streams as a line coverage and their classification by stream order; the zones used for this study (state and county; hydrologic units [at the 4, 8 and 12 scales]); and, lake watersheds (IWS). We also include boundaries of U.S. stat

opencc-by-4.0Jul 2022View details →

Data and R code for long-term study of fire and climate effects on water quality in Clear Lake, California

Long-term relationships between water quality, fire and climate for Clear Lake, California. Although the watershed has historically experienced frequent fire, the 2018 Mendocino Complex, which was the largest wildfire complex in state history, burned approximately 40% of the watershed, sparking concerns about drinking water quality and lake ecosystem health. This analysis spans approximately 1968-2021.

opencc-by-4.0Oct 2022View details →

Lake Cadagno 2017 CTD and water quality monitoring

This repository contains an almost bi-daily CTD (conductivity, temperature and depth) and water quality profile dataset conducted during the Summer of 2017 in Lake Cadagno, Ticino (TI), Switzerland. Associated publications: <ul> <li> Sepúlveda Steiner, O., Bouffard, D. and Wüest, A. (2021). Persistence of bioconvection-induced mixed layers in a stratified lake. Limnol Oceanogr, 66: 1531-1547. <a href="https://doi.org/10.1002/lno.11702">https://doi.org/10.1002/lno.11702</a> [Check this publication for temperature-corrected conductivity (e.g., C_20) and water density calculations specific to Lake Cadagno] </li> <li> Janssen, D. J., Rickli, J., Wille, M., Sepúlveda Steiner, O., Vogel, H., Dellwig, O., et al. (2022). Chromium cycling in redox-stratified basins challenges δ53Cr paleoredox proxy applications. Geophys. Res. Lett., 49, e2022GL099154. <a href="https://doi.org/10.1029/2022GL099154">https://doi.org/10.1029/2022GL099154</a> </li> </ul>

opencc-by-4.0Dec 2018View details →

Fig. 3. Correlation coefficients estimated between water quality indicators and morphological Fig. 4 in Investigation Of Common Reed Regrowth On The Shores Of Recreational Lakes

Fig. 3. Correlation coefficients estimated between water quality indicators and morphological Fig. 4. The number of holidaymakers near parameters of common reeds on the shores of Bridvaisis, Gaustvinis and Gilius lakes (in the Bridvaisis, Gaustvinis and Gilius Lakes. The order from the bottom to the top) and differences boundary of the continuous line side indicates in morphological parameters of plants after the cases where p <0.01; dashed lines, where p <0.05. holidaymakers' visits.

opencc-by-4.0Oct 2018View details →

EOMORES earth observation and in situ data of water quality in lakes and coastal areas - year 1

EOMORES is a European innovation project aiming to develop commercial services for monitoring the quality of inland and coastal water bodies, using data from Earth Observation (EO) satellites and in situ sensors to measure, model and forecast water quality parameters. The current data set is a sample of the data generated within the first project year (2017), and consists of Earth Observation (EO) data and in situ data from lakes and coastal areas. For full data sets, please contact the respective contact point listed for each area. Data sets of the second (2018) and third (2019) year of EOMORES will also be submitted. The following is included: - Estonia lakes and coast: in situ data 2017 - Finland: links to repositories of EO data - Italy Trasimeno: sample of EO data 2017 - Lithuania Curonian Lagoon: sample of EO data 2017 - Netherlands Lake Markermeer: sample of EO data 2017 - Netherlands Lake Paterswoldsemeer: EO data 2015, 2016, 2017 - UK Scotland: in situ data Loch Leven and Loch Lomond 2017 - UK WCO Sentinel2A match ups: Western Channel Observatory match ups with Sentinel-2 satellite 2016, 2017 http://eomores-h2020.eu

opencc-by-4.0Sep 2021View details →

EO-derived water quality parameters using aerial imaging spectrometry for Lake Mulargia (Sardinia, Italy) (2020/09/24)

This dataset contains Hyspex-derived water quality (WQ) products of Lake Mulargia (Sardinia, Italy) for the 24 September 2020. The acquisition was done by CGR Spa (Italy). 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).

openCC (other)Dec 2022View details →

Summer Water Quality Data from four ponds at Grafton Lakes State Park, New York, United States: 2022

Lake water quality data was collected on four ponds in Grafton Lakes State Park, NY, USA to establish long-term monitoring sites. Samples were collected once a month from May to July of 2022. Temperature and dissolved oxygen profiles were collected using a YSI Sonde. Secchi disk depths were recorded during the July sampling event.

openCC (other)Jan 2023View details →

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.

openCC (other)Jan 2023View details →

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.

openCC (other)Jan 2019View details →

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.