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56 results for “lake water chemistry”
Stream and lake water chemistry data for Green Lakes Valley, 1998 - ongoing.
This is a summary of major ion concentrations for lake water at selected depths as well as for the inlets and outlets of Green Lakes 1, 4, and Lake Albion. On some occasions the same samples were also taken from other lakes in the Green Lakes Valley, such as Green Lakes 2, 3 and 5.
Stream water chemistry data for Green Lake 4, 1982 - ongoing.
This is a summary of major ion concentrations for water samples collected at Green Lake 4. Under summer conditions (June - October) samples were from the outlet stream from the lake; in winter (November - May) they were from the lake, beneath ice cover.
Stream water chemistry data for Green Lake 5 Rock Glacier, 1998 - ongoing.
This is a summary of major ion concentrations for stream water samples collected at the Green Lake 5 Rock Glacier, near Green Lake 5 in the Boulder County Watershed Green Lakes Valley.
Summer water chemistry; sediment phosphorus fluxes and sorption capacity; sedimentation and sediment resuspension dynamics; water column thermal structure; and zooplankton, macroinvertebrate, and macrophyte communities in eight shallow lakes in northwest Iowa, USA (2018-2020)
The primary aim of this data product is to characterize change in water chemistry, sediment-water interactions, and biological communities in shallow, eutrophic lakes undergoing a fishery biomanipulation. We studied eight glacial lakes located in northwest Iowa, USA, from 2018 to 2020 during the summer season (May to September). A subset of these lakes (n = 4; Center, Five Island, North Twin, and Silver Lakes) were part of a fishery biomanipulation in which the Iowa Department of Natural Resources (IDNR) incentivized commercial harvest of common carp (Cyprinus carpio) and bigmouth buffalo (Ictiobus cyprinellus). Harvests occurred in Center and Five Island Lakes during 2018-2019 and in North Twin and Silver Lakes during 2019-2020. Between 73 and 373 kg fish biomass per ha were removed each year. The other study lakes (n = 4; Blue, South Twin, Storm, and Swan Lakes) remained unmanipulated during the study period. Over the course of the biomanipulation, we quantified a suite of physical, chemical, and biological parameters across the study lakes. High frequency aquatic sensors were used to measure water column thermal structure, dissolved oxygen concentrations, and algal pigments. Manual water chemistry sampling further quantified suspended solids, total phosphorus and nitrogen, soluble reactive phosphorus, nitrate, and water clarity. We measured flux rates of phosphorus between bottom sediments and the overlying water using ex situ sediment core incubations under both oxic and anoxic conditions. We further quantified sediment phosphorus sorption capacity using equilibrium phosphorus concentration assays. Tiered sediment traps were used to measure sedimentation rates as well as sediment resuspension in bottom waters. We also measured change in zooplankton, macroinvertebrate, and macrophyte community composition and abundance. These data will be used to better understand the mechanisms of internal phosphorus loading in shallow lakes and the ecosystem effects of fisherie
LAGOS-US LIMNO: Data module of surface water chemistry from 1975-2021 for lakes in the conterminous U.S.
The LAGOS-US LIMNO data package is one of the core data modules of LAGOS-US, an extensible research-ready platform designed to study the 479,950 lakes and reservoirs larger than or equal to 1 ha in the conterminous US (48 states plus the District of Columbia). The LIMNO module contains in situ observations of 47 parameters of lake physics, chemistry, and biology (hereafter referred to as chemistry) from lake surface samples (defined as observations taken from the epilimnion of a lake) obtained from the Water Quality Portal, the National Lakes Assessment (2007, 2012, 2017), and NEON programs. LIMNO provides 3,511,020 observations across all parameters collected between 1975 and 2021 from 20,329 lakes; the number of observations per lake ranged from 1 to 20,605 with a median of 32. The database design that supports the LAGOS-US research platform was created based on several important design features: lakes are the fundamental unit of consideration, all lakes in the spatial extent above the minimum size must be represented, and most information is connected to individual lakes. The design is modular, interoperable (the modules can be used with each other, as well as other comprehensive lake data products such as the USGS NHD), and extensible (future database modules can be developed and used in the LAGOS-US research platform by others). Users are encouraged to use the other two core data modules that are part of the LAGOS-US platform: LOCUS (location, identifiers, and physical characteristics of lakes and their watersheds) and GEO (characteristics defining geospatial and temporal ecological setting quantified at multiple spatial divisions) that are each found in their own data packages.
Water chemistry data for various lakes near Toolik Research Station, Arctic LTER. Summer 2010 to 2021
Note: Corrections were made to Particulate phosphorus values. See version 5 notes. Decadal file describing the water chemistry in various lakes near Toolik Research Station (68 38'N, 149 36'W) during summers from 2010 to 2021. Chemical analyses were conducted on samples from various depths in the sample lakes either once, or multiple times during the spring, summer and fall months (May to September). Chemical analyses for the samples include alkalinity, dissolved organic and inorganic carbon, inorganic and total dissolved nutrients, particulate carbon, nitrogen and phosphorous, cations and anions.
Spatial surface water chemistry of Lake Mendota with FLAMe: 2014-2016
We mapped surface water chemistry in Lake Mendota 39 times between 2014 and 2016. We used a sensor-based and boat-mounted sensing platform to continuously measure underway water chemistry. Measurements were linked with global positioning systems (GPS) to create maps of surface water chemistry. Data have been provided in three formats (raw, hydraulic-corrected, and tau-corrected). Dataset is used for the publication, "Large spatial and temporal variability of carbon dioxide and methane in a eutrophic lake", https://doi.org/10.1029/2019JG005186
North Temperate Lakes LTER Regional Survey Water Chemistry 2015 - current
The Northern Highlands Lake District (NHLD) is one of the few regions in the world with periodic comprehensive water chemistry data from hundreds of lakes spanning almost a century. Birge and Juday directed the first comprehensive assessment of water chemistry in the NHLD, sampling more than 600 lakes in the 1920s and 30s. These surveys have been repeated by various agencies and we now have data from the 1920s (UW), 1960s (WDNR), 1970s (EPA), 1980s (EPA), 1990s (EPA), and 2000s (NTL). The 28 lakes sampled as part of the Regional Lake Survey have been sampled by at least four of these regional surveys including the 1920s Birge and Juday sampling efforts. These 28 lakes were selected to represent a gradient of landscape position and shoreline development, both of which are important factors influencing social and ecological dynamics of lakes in the NHLD. This long-term regional dataset will lead to a greater understanding of whether and how large-scale drivers such as climate change and variability, lakeshore residential development, introductions of invasive species, or forest management have altered regional water chemistry. The regional lakes survey in 2015 followed the standard LTER protocol for standard water chemistry and biology. Samples were taken as close to solar noon as possible. Seven lakes had replicates performed, which were chosen at random.
Summer water chemistry, high frequency sensors, zooplankton and benthic macroinvertebrate community composition, periphyton, fish, and macrophyte biomass, along with lake metabolism and greenhouse gas dynamics in six experimental ponds in central Iowa, USA (2020)
This data product contains physical, chemical, and biological data ranging from the minute to daily to weekly scale in six artificial ponds (400 square meter surface area, 2m depth) in central Iowa (USA) 2020. Ponds were paired into three sets of treatment and reference with treatment ponds receiving two nutrient pulses designed to increase ambient phosphorus concentrations ~ 3 - 5%. Nitrogen and phosphorus were added as NH4NO3 and H3PO4, respectively, at a 24:1 molar ratio. The first nutrient pulse occurred on Julian day of year (DOY) 176 corresponding to a 3% increase and the second nutrient pulse occurred on DOY 211 to a 5% increase. Each treatment-reference set had a different food web structure established ranging between low, intermediate, and high complexity based on trophic connectivity and food chain length. Added to this data package is a document titled "2020 Iowa State University Horticultural Farm Experimental Ponds Nutrient Addition Experiment". For experimental set up, context, and a summary table of the data tables archived herein with available variables please review this document. It is added to aid in successful interpretation and to increase ease-of-use. Please email Tyler Butts (tyler.james.butts@gmail.com) for any and all questions regarding context or use of this dataset!
Stream metabolism estimates and surface water chemistry in Glenbrook Creek (NV) and Blackwood Creek (CA) in the Lake Tahoe Basin, 2021-2024
The goal of this project was to develop a process-based understanding of how in-stream productivity and nitrogen dynamics respond to hydroclimatic volatility. We used a combined approach of high-frequency sensor deployment and maintenance, ecosystem metabolism modeling, and routine monitoring of water chemistry and other parameters. The data we collected as part of this project demonstrate how variable ecosystem productivity is in time and space in within and among mountain streams. Although maintenance of the sensor arrays during the exceptionally wet winter of 2023 was challenging, we were able to estimate a time series of stream metabolism within the upper and lower reaches of two streams with different basin characteristics and through hydroclimatic conditions (2021 to 2024). Throughout this project we: 1. We generated four years of daily estimates of ecosystem metabolism (gross primary productivity, ecosystem respiration, and net ecosystem productivity) from upper and lower reach stations on both the east and west shores of the Lake Tahoe Basin. 2. We measured ammonium (NH4+) and nitrate (NO3-) concentrations in surface water and sediment samples from both Glenbrook and Blackwood creeks. 3. We modeled nitrogen supply and demand dynamics at each reach location. See this git code repository for project analysis: https://github.com/kellyloria/Mountain-stream-biogeochem-and-productivity.
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.
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.
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 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 chemistry of LTER-Europe research site Lake Paione Inferiore LTER_EU_IT_088 (1984-2013)
<p>This dataset provides information about water chemical parameters for Lake Paione Inferiore LTER_EU_IT_088: pH, Total alkalinity, conductivity, total nitrogen, major cations (calcium, magnesium, sodium, potassium), major anions (sulphate, nitrate, chloride) and silica for the period 1984-2013.</p> <p>Lake Paione Inferiore (LPI) is a high altitude Alpine lake, located at 2002 m a.s.l. in the Bognanco Valley, Province of Verbania, Piedmont Region, Italy. It has a surface area of 0.86 ha and a maximum depth of 13.5 m. The Lake, together with Lake Paione Superiore (LPS), is included in the monitoring sites of the UN-ECE Program ICP WATERS (International Cooperative Programme on Assessment and Monitoring of Acidification of Rivers and Lakes) for which the CNR Water Research Institute is the National Focal Centre for Italy.</p> <p>This dataset includes the following files: Metadata LTER_EU_IT_088.xls and per each parameter one xls file with data records. Dataset for water chemistry of LPI for the period 2014-2020 is available at <a href="https://doi.org/10.5281/zenodo.10519349">https://doi.org/10.5281/zenodo.10519349</a></p> <p>Detailed description of the site LPI is available at https://deims.org/c128d2f9-beb0-45ba-89bb-df9e12f95b0f</p>
Water chemistry of LTER-Europe research site Lake Paione Superiore LTER_EU_IT_089 (1984-2013)
<p>This dataset provides information about water chemical parameters for Lake Paione Superiore LTER_EU_IT_089: pH, Total alkalinity, conductivity, total nitrogen, major cations (calcium, magnesium, sodium, potassium), major anions (sulphate, nitrate, chloride) and silica for the period 1984-2013.</p> <p>Lake Paione Superiore (LPS) is a high altitude Alpine lake, located at 2269 m a.s.l. in the Bognanco Valley, Province of Verbania, Piedmont Region, Italy. It has a surface area of 0.68 ha and a maximum depth of 11.5 m. The Lake, together with Lake Paione Inferiore (LPI), is included in the monitoring sites of the UN-ECE Program ICP WATERS (International Cooperative Programme on Assessment and Monitoring of Acidification of Rivers and Lakes) for which the CNR Water Research Institute is the National Focal Centre for Italy.</p> <p>This dataset includes the following files: Metadata LTER_EU_IT_089.xls and per each parameter one xls file with data records.</p> <p>Detailed description of the site LPS is available at https://deims.org/7e5837a9-ee27-4e27-822a-f50e5217c313</p> <p>Dataset for water chemistry of LPS for the period 2014-2020 is available at https://doi.org/10.5281/zenodo.10519126</p>
Marcell Experimental Forest biweekly surface water and monthly porewater chemistry at Bog Lake Peatland, 2007 - ongoing
This data set reports the chemistry of surface and porewater water from the Bog Lake peatland in the Marcell Experimental Forest (MEF) in Itasca County, Minnesota, which is operated and maintained by the USDA Forest Service, Northern Research Station. Surface water has been collected about every other week since 2007 from a pool of water and sampling is ongoing. Once covered with ice, water was typically sampled once a month. Porewaters at five depths (0 to 2 m depths) have been collected about monthly from three different nest of piezometers since 2013, though never when samplers were frozen. Samples are measured for pH, specific conductivity, anions (chloride, sulfate), cations (calcium, magnesium, potassium, sodium, aluminum, iron, manganese, strontium), silicon, nutrients (ammonium, nitrate, soluble reactive phosphorus, total nitrogen, total phosphorus), and total organic carbon.
Water chemistry data for various lakes near Toolik Research Station, Arctic LTER. Summer 2000 to 2009.
Decadal file describing the water chemistry in various lakes near Toolik Research Station (68 38'N, 149 36'W) during summers from 2000 to 2009. Chemical analyses were conducted on samples from various depths in the sample lakes either once, or multiple times during the spring, summer and fall months (May to September). Chemical analyses for the samples include alkalinity, dissolved organic and inorganic carbon (DIC/DOC), inorganic and total dissolved nutrients (NH4, PO4, NO3, TDN, TDP), particulate carbon, nitrogen and phsphorous (PC, PN, PP), cations (Ca, Mg, K, Na and Si) and anions (SO4, Cl). See methods for the yearly datsets which were combined into this data set.
Water chemistry data for various lakes near Toolik Research Station, Arctic LTER. Summer 1990 to 1999.
Decadal file describing the water chemistry in various lakes near Toolik Research Station (68 38'N, 149 36'W) during summers from 1990 to 1999. Chemical analyses were conducted on samples from various depths in the sample lakes either once, or multiple times during the spring, summer and fall months (May to September). Chemical analyses for the samples include alkalinity, dissolved organic and inorganic carbon (DIC/DOC), inorganic and total dissolved nutrients (NH4, PO4, NO3, TDN, TDP), particulate carbon, nitrogen and phsphorous (PC, PN, PP), cations (Ca, Mg, K, Na and Si) and anions (SO4, Cl). See methods for the yearly datsets which were combined into this data set.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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International Brain Laboratory public data
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OpenNeuro
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