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19,365 results for “watering”
North Temperate Lakes LTER: High Frequency Water Temperature Data - Lake Mendota Buoy 2006 - current
The instrumented buoy on Lake Mendota is equipped with a thermistor chain that measures water temperature. In 2006, the thermistors were placed every half-meter from the surface through 7m, and every meter from 7m to 15m. Since 2007, the thermistors were placed every half-meter from the surface through 2m, and every meter from 2m to 20m. The sensor at the water surface is as close to the surface as feasible. A list of sensors used since the first deployment in 2006 is provided as a downloadable CSV file. Hourly and daily water temperature averages are computed from high resolution (1 minute) data.The buoy is removed during the winter when the lake is ice-covered (typically Dec-Apr). Meteorological and limnological data collected at the same buoy site can be found in an ancillary dataset. Sampling Frequency: one minute. Number of sites: 1. Location lat/long: 43.0995, -89.4045 Notes: The thermistor string failed in June 2014, so there is not data between June 17, 2014 and the start of the 2016 season. The thermistor string failed again in August 2023. It was replaced by Hobo temp loggers at 0, 5,10, 15, 20 meters depth for the remainder of 2023.
Lake Mendota long term water quality model
The data are associated with the following manuscript: Hanson, P. C., Ladwig, R., Buelo, C., Albright, E. A., Delany, A. D., & Carey, C. (2023). Legacy phosphorus and ecosystem memory control future water quality in a eutrophic lake. Lake water and ice observational data and lake bathymetry are from the North Temperate Lakes Long Term Ecological Research program. Brief abstract of the work: To investigate how water quality in Lake Mendota might respond to nutrient pollution reduction, we used computer models to simulate the elimination of phosphorus inputs from the catchment and track water quality change. The data herein are used to drive and calibrate the model. In addition, model code and simulation output are included as "other entities."
Greenhouse gas and water chemistry data from urban ponds in Madison, Wisconsin during the summer and under-ice period of 2021-2022
Stormwater ponds are common features in urbanized landscapes and can suffer from rapid oxygen depletion when thermally stratified or ice-covered. To investigate under-ice oxygen dynamics and drivers of bottom water oxygen saturation, we sampled 20 stormwater ponds in Madison, Wisconsin, USA during the summer of 2021 and winter 2022. The urban ponds ranged in age, shape, size, and depth. We repeatedly took YSI profiles of water temperature, oxygen, and specific conductance 7 times in the summer and 3 times in the winter. Water chemistry variables were collected in the surface waters, habitat surveys were conducted in the summer, and ice/snow thickness was recorded in the winter. We also measured the concentration of greenhouse gases in the surface waters as a consequence to oxygen depletion using the headspace equilibrium method.
LakeBeD-US: Ecology Edition - a benchmark dataset of lake water quality time series and vertical profiles
LakeBeD-US: Ecology Edition is a harmonized lake water quality dataset containing time series and vertical profiles of 21 lakes in the United States monitored by long-term monitoring institutions. These institutions include the North Temperate Lakes Long-Term Ecological Research program (NTL-LTER), Niwot Ridge Long-Term Ecological Research program (NWT-LTER), National Ecological Observatory Network (NEON), and the Carey Lab at Virginia Tech as part of the Virginia Reservoirs Long-Term Research in Environmental Biology (LTREB) site in collaboration with the Western Virginia Water Authority. The data include depth-discrete observations of 17 water quality variables including temperature, dissolved oxygen, chemical properties, Secchi depth, and more. Observations are divided into data collected by automated sensors at a relatively high temporal frequency and manually sampled data at a relatively low temporal frequency. All data were collected in situ. The data are available as Apache Parquet files, and the included R scripts give guidance on how to utilize and query the dataset in R. LakeBeD-US: Ecology Edition is an ecological science-oriented companion to LakeBeD-US: Computer Science Edition. The Computer Science Edition is available on the Hugging Face Hub.
North Temperate Lakes LTER: Multiparameter Water Quality Data -- CFL Pier, Lake Mendota.
This is data from a SUNA V2 nitrate sensor and a YSI EXO 2 sonde instrumented with water temperature, dissolved oxygen, pH, chlorophyll, phycocyanin, conductivity, turbidity, and fDOM sensors. The sensors are located at the lake end of the pier serving the Center for Limnology on the UW-Madison campus. The YSI sonde is fixed on the pier with sensors nominally at 0.5 meters depth, while the SUNA is suspended below the pier at one meter depth in the open water season. In the winter season, the SUNA is placed in a cage on the lake bottom close to shore with the sensor 18cm off the bottom. The depth of the sensors will vary with lake level over the season. The water depth at the lake end of the pier is normally about 3 meters. YSI sonde data are sampled once per minute. Hourly and daily averages are provided as separate CSV files. The SUNA sample rate varies. In the winter (under the ice) it relies on single battery charge, so the wiper is deactivated and the sensor samples every 1-2 hours. Daily averages of SUNA are also provided as a separate CSV. The YSI sonde is deployed only during the ice-free season coinciding with the placement of the pier. Sensors are cleaned and maintained roughly every two weeks. Number of sites: 1. Location lat/long: 43.07758, -89.40297
North Temperate Lakes LTER: High Frequency Water Temperature Data - Sparkling Lake Raft 1989 - current
The instrumented raft on Sparkling Lake is equipped with a thermistor chain that measures water temperature from depths ranging from the surface to 18m at an interval of 0.5m near the surface to a one-meter interval throughout the rest of the water column. The surface temperature sensor is attached to a float so it's as close to the surface as feasible. Sampling frequency is currently one minute with hourly and daily averages provided. Number of sites: 1
North Temperate Lakes LTER: High Frequency Water Temperature Data - Trout Bog Buoy 2003 - current
The instrumented buoy on Trout Bog is equipped with a thermistor chain that measures water temperature from depths ranging from the surface to 7m placed every 0.5-1m throughout the water column. From the initial deployment in 2003 through 2014, a surface buoy was used in the open water season. Since 2015, a subsurface buoy has been used, including under-ice deployments during the winter. Recorded depths can vary slightly depending on specifics of the year's deployment hardware. The sampling frequency:varies for instantaneous samples. Prior to 2011, the sample frequency was every 10 minutes, with some short periods of 2 minutes in 2003. Beginning in 2011, the sample frequency has been one per minute. Hourly and daily averages are also provided. Number of sites: 1.
Stream water chemistry data for Green Lake 5 outlet, 1984 - ongoing.
This is a summary of major ion concentrations for stream water samples collected from the outlet stream at Green Lake 5.
Stream water chemistry data for Lake Albion inlet, 1984 - 2004.
This is a summary of major ion concentrations for stream water samples collected at the old parshall flume at the inlet to Lake Albion.
Stream water chemistry data for Navajo meadow, 1984 - ongoing.
This is a summary of major ion concentrations for stream water samples collected at the flow gauging site at the lower end of the Navajo meadow. Marked by rebar in channel.
Stream water chemistry data for Lake Albion spillway, 1984 - 2004.
This is a summary of major ion concentrations for stream water samples collected at the spillway from Lake Albion. At times when the lake level was below the spillway, no samples were taken.
Water oxygen-18 and deuterium data for Green Lakes Valley, 1989 - 1990.
Isotopic signatures of deuterium and delta-O18 ratios were determined for surface flow, groundwater, and precipitation samples collected from within the Green Lakes Valley in 1990. Surface water was collected from lake inlets, lake outlets, and streams. Groundwater was collected in zero-tension and tension samplers at several depths from within several soil series and topographic situations.
Ground water well elevation for Niwot Ridge Saddle, 2012 - 2018.
Water level of Saddle Ground Water Wells. Ground Water Well locations, depths, and design were determined by Niwot Ridge LTER lead researchers, Mark Williams and Nel Caine, to monitor groundwater chemistry and water levels. Well locations were selected based on proximity to the headwater region of the Saddle stream channel. Ground Water Wells are located along an east-west transect at the Saddle site, each pair consisting of a deep well to a depth between 6.3 and 8.8 m, and a shallow well to a depth of 1.5 m. Ground surface elevations at the Saddle wells range from about 3522 m at the eastern wells to 3532 m at the western wells. The transect is roughly 170 m from east to west, has an average slope of 0.06, and is perpendicular to the Saddle stream. Saddle pair 3 was installed very close to the channel. Saddle pairs 2 and 4 were installed on opposite sides of the channel. Saddle pair 1 was installed furthest from the channel (King, 2012). Ground water wells were installed in October 2005 by Bandimere Geothermal Drilling Systems. Wells are cased with 2-inch nominal pipe size, Schedule 40 polyvinyl chloride (PVC), flush-threaded pipe. Well screens were constructed from 0.020-inch continuous slot PVC and installed in 5-ft (1.52 m) intervals. All of the wells have 1.52 m screens at the bottom of the well. The bottoms of the wells were capped with a PVC flush-threaded point cap. The annular space around each screen and pipe was backfilled with #10-20 silica sand to act as a filter (King, 2012). The Niwot Ridge LTER monitoring of these Ground Water Wells has varied over the years since the wells were installed. Prior to 2014, all wells were sampled weekly in summer and monthly in winter for chemistry, and alternating wells were monitored for water level with pressure transducers and a weighted tape measure. From 2015 through present, Saddle Deep 3 (SD3) and Saddle Deep 4 (SD4)- those located closest to the Saddle Stream headwaters- are being monitored for water level, wat
Water Tower Index for Saddle Catchment, 2000 - 2018.
The Saddle Catchment of the Niwot Ridge LTER experiences significant spatial variation regarding snow distribution and, in turn, the timing and amount and surface water input generation (i.e., rainfall and snowmelt). In winter months and in areas that receive a high amount of redistributed snow (via wind), snow accumulation is large and the snowpack persists until the snowmelt season, creating a lag between the timing of precipitation (as snow) and the timing of surface water inputs (as snowmelt). Alternatively, areas that are scoured of snow, retain little snow. In these areas, rain is the primary source of surface water inputs, and thus there is little/no lag in the timing of precipitation and surface water inputs (as rain). The lag in the timing of precipitation and surface water inputs in the wind deposition zones, however, is critical to providing water to the surrounding and downstream environments later in the year. The snow in these areas thus act as a natural water tower to retain water (as snow) until the snowmelt season. To capture the timing and magnitude of the delay between precipitation and surface water inputs, a Water Tower Index (WTI) was generated. The WTI uses equations (see Methods) to fit a sine curve to annual precipitation (P) and annual surface water inputs (SWI). A third equation then compares to the phase and amplitude of the two sine curves, generating a metric between -1 and 1. Positive WTI values signify P and SWI out of temporal alignment (where WTI = 1 indicates strong (i.e., high amplitude) temporal misalignment between P and SWI). Negative WTI values signify P and SWI in temporal alignment (where WTI = -1 indicates strong (i.e., high amplitude) temporal alignment between P and SWI). P and SWI data were taken from DHSVM output run by Nels Bjarke, which included 19 years of information (WY2000-WY2018). The methodology was applied, spatially, across the Saddle Catchment of the Niwot Ridge LTER. In turn, this dataset reveals, importantl
Spatial distribution of snow water equivalent for the Niwot Ridge, 1996 - 2019
This dataset provides a daily estimation of snow water equivalent for the Niwot Ridge during snow melting period from 1997 to 2019 at 30-meter spatial resolution. The dataset includes two series of SWE data: 1) 1996-2007 daily SWE dataset is generated by Jepsen et al., (2012); 2) 2008-2019 daily SWE dataset is generated by Dr. Kehan Yang following the same method used by Jepsen et al., (2012). In brief, a physically based reconstruction model is used to calculate daily SWE backward from snow disappearance date to peak snow accumulation. The infilled hourly climate data set for C1, Saddle and D1 (data available at https://portal.edirepository.org/nis/mapbrowse?packageid=knb-lter-nwt.168.2) is interpolated and used as the meteorological forcing in the snow energy balance calculation of SWE reconstruction. The shortwave radiation is estimated by downscaling hourly product of the Geostationary Operational Environmental Satellite (GOES) using TOPORAD tool. The USGS Landsat Level-3 fractional snow-covered area product is used to proportion potential energy flux for snowmelt at the pixel scale. Please see detailed methods included with this data package for more details and references.
Benthic macroinvertebrate, water temperature, and stream environmental data for Green Lakes Valley, 2021.
This dataset contains stream benthic macroinvertebrate community structure data from nine sites in the Green Lakes Valley ranging from below treeline near Albion Camp to the outflow of the Arikaree Glacier, all sampled in summer of 2021. The dataset also contains files with stream environmental data related to substrate stability, periphyton chlorophyll a concentrations, and water temperatures.
Chlorophyll and phaeopigments from water column samples, collected at selected depths at Palmer Station Antarctica, during the Palmer LTER field seasons, 1991-2025.
Phytoplankton chlorophyll sampling was led by Smith from the 1991-1992 season through the 2001-2002 season, and then by Vernet from the 2002-2003 season through the 2006-2007 season. Schofield is the third, and current lead, beginning in the 2008-2009 season. Methods have been kept consistent as much as possible over the full time series and different Principal Investigators. Chlorophyll a (Chl a) is the principal photosynthetic pigment of phytoplankton, and is used as a proxy measurement for estimating phytoplankton biomass in water samples. Chl a concentrations reflect the distribution of active phytoplankton spatially and with depth in the water column and their changes over time. Phaeopigments are non-photosynthetic pigments that are degradation products of phytoplankton chlorophylls which form during and after phytoplankton blooms. Water samples are collected throughout the water column at stations within the Palmer LTER region (primarily B and E, to 50m and 65m respectively). Beginning in the 2020-2021 season, Station B is no longer sampled. Chlorophyll and phaeopigment concentrations are determined by filtration, extraction, and fluorometric detection of samples. The primary source of error for phaeopigment measurement is Chlorophyll b. If high amounts of Chlorophyll b are present in the sample, phaeopigments may be overestimated. There was no field season in 2021-2022.
Water column primary production from inorganic carbon uptake for 24h at simulated in situ light levels in deck incubators, collected at Palmer Station Antarctica during Palmer LTER field seasons, 1994-2025.
Primary Production experiments were led by Vernet from the 1994-1995 season through the 2006-2007 season. Schofield is the current lead, beginning in the 2009-2010 season. Methods have been kept consistent as much as possible over the full time series and different Principal Investigators. Primary production is the uptake of inorganic carbon and assimilation of it into organic matter by phytoplankton. Primary production rates, expressed as mgC per m3 per day were measured by the uptake of radioactive (14C) sodium bicarbonate. Water samples are collected throughout the water column at stations within the Palmer LTER region (primarily B and E, to 50m and 65m respectively). Beginning in the 2020-2021 season, Station B is no longer sampled. Water is put into borosilicate bottles, inoculated with 1 uCi of NaH14CO3 per bottle, and incubated in an outdoor deck incubator. The incubator is plumbed to the Palmer Station sea water system to maintain ambient seawater temperature and bottles are screened to in situ light levels. The uptake of 14C-bicarbonate by the phytoplankton was measured in a scintillation counter after a 24-hour incubation period. Primary production experiments were not conducted during the 2020-2021 nor 2023-2024 field seasons. There was no field season in 2021-2022.
Photosynthetic pigments of water column samples analyzed using High Performance Liquid Chromatography (HPLC), sampled during the Palmer LTER field seasons at Palmer Station, Antarctica, 1991 – 2023.
Phytoplankton pigment sampling was led by Prezelin from the 1991-1992 season through the 1993-1994 season, and then by Vernet from the 1994-1995 season through the 2006-2007 season. Schofield is the third, and current lead, beginning in the 2008-2009 season. Methods have been kept consistent as much as possible over the full time series and different Principal Investigators. Phytoplankton have a suite of accessory pigments in addition to Chlorophyll a, including other Chlorophyll’s (e.g. Chlorophyll b), Xanthophylls, and Carotenes. These accessory pigments can be used as chemotaxonomic markers to assess the composition and distribution of the phytoplankton community. For example, Fucoxanthin is a marker pigment of Diatoms, whereas Alloxanthin is a marker pigment of Cryptophytes. Accessory pigments also assist in photoacclimation and photoprotective processes. Water samples are collected throughout the water column at stations within the Palmer LTER region (primarily B and E, to 50m and 65m respectively). Water samples are filtered onto GF/F filters, and filters kept frozen at -80C until analysis. HPLC analysis is completed following Wright et al (1991). Following the guidelines set by NASA SeaHARRE, we use an internal standard and replicate injects on the HPLC to track recovery and replicability of the pigment extraction methods. Data is unavailable for the Palmer 2009-2010 season due to instrumentation problems and for the Palmer 2011-2012 season due to a freezer failure which resulted in the loss of samples. There is a temporary data gap for the Palmer 2015-2016, Palmer 2016-2017, Palmer 2019-2020, Palmer 2020-2021, and Palmer 2023-2024 seasons because those samples have not been analyzed yet.
Chlorophyll and phaeopigments from water column samples, collected at selected depths aboard Palmer LTER annual cruises off the coast of the Western Antarctic Peninsula, 1991-2024.
Phytoplankton chlorophyll sampling was led by Smith from 1991-2002, and then by Vernet from 2003-2008. Schofield is the third, and current lead, beginning in 2009. Methods have been kept consistent as much as possible over the full time series and different Principal Investigators. Chlorophyll a (Chl a) is the principal photosynthetic pigment of phytoplankton, and is used as a proxy measurement for estimating phytoplankton biomass in water samples. Chl a concentrations reflect the distribution of active phytoplankton spatially and with depth in the water column and their changes over time. Phaeopigments are non-photosynthetic pigments that are degradation products of phytoplankton chlorophylls which form during and after phytoplankton blooms. Water samples are collected throughout the water column along the Western Antarctic Peninsula at regular LTER grid stations where CTD casts are preformed and in surface waters at underway stations, where CTD casts are not done, using the ship's flow-through seawater system. Chlorophyll and phaeopigment concentrations are determined by filtration, extraction, and fluorometric detection of samples. The primary source of error for phaeopigment measurement is Chlorophyll b. If high amounts of Chlorophyll b are present in the sample, phaeopigments may be overestimated.
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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