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56 results for “water ponding”
Metabolism and water chemistry of tundra ponds near Utqiagvik, Alaska, 2019–2024
Low centered polygon ponds and thermokarst trough ponds were sampled near Utqiagvik, AK in late summer from 2009-2024 to understand how pond types differ in chemistry and C flux. Water samples from open water were characterized for nutrients concentration and algal biomass. Carbon and oxygen concentrations were monitored continuously using sensors.
High-Frequency and Water Quality Monitoring Data of Long Pond at Grafton Lakes State Park, New York, United States, 2024
This collection of datasets contains high frequency data captured through Hobo, Minidot, and water level sensors, as well as data collected from manual sampling days. Long Pond is located in Grafton New York, USA named for its long shape and shallower depth (max depth is around 8 meters). Using a buoy, sensors were attached to a rope at the deepest point discoverable and deployed. Data covers all information recorded from 2024-04-30 to 2024-10-09. Times are recorded in Eastern Standard Time. Temperature Readings were taken every 10 minutes at 1 meter intervals by both Minidots and hobo sensors (1.52-7.52 m). Dissolved Oxygen was similarly collected every 10 minutes by the Minidots at depths 1.52, 6.52, and 7.52 meters. Manual measurements (YSI and Secchi disk) were recorded on sampling days, as well as water samples that were assessed for water quality parameters from the top and bottom of the lake. Water level data was also collected in 12 hour intervals.
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!
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.
Greenhouse Gas and Water Chemistry Data from Ponds in the Twin-Cities area of Minnesota, 2021
Freshwaters are significant contributors of greenhouse gases to the atmosphere, including carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Small waterbodies such as ponds are now recognized to have disproportionate greenhouse gas emissions relative to their size, but recorded emissions from ponds have varied by several orders of magnitude. To assess drivers of variation in pond greenhouse gas dynamics, this study measured concentrations and emissions of CO2, CH4, and N2O across 26 ponds in Minnesota, USA during the ice-free season. The studied ponds ranged in land-use, from urban stormwater ponds to natural forested ponds. Water chemistry variables were measured with sonde profiles as well as surface water samples. Greenhouse gas emsisions of CO2 and CH4 were measured with a floating chamber at three locations on each pond, and gas concentrations of CO2, CH4, and N2O were measured using a headspace equilibrium technique in both the surface waters and bottom waters of each pond.
PIE LTER chlorophyll concentrations in the surface waters and sediments of six high marsh ponds, Rowley, MA, during the summer of 2016.
We measured chlorophyll concentrations in the surface waters and sediments of six ponds in three regions of the PIE-LTER marshes during summer 2016. The goal was to assess whether pond microalgal community abundances varied predictably with pond dimensions (e.g., surface area, volume) or geographic attributes (e.g., elevation, distance from upland, marsh region). Samples were collected from several locations in each pond in order to capture spatial heterogeneity.
PIE LTER 15-minute surface water dissolved oxygen, temperature, and salinity of six high marsh ponds, Rowley, MA, during the summer of 2016.
We estimated the oxygen metabolism of six ponds in three regions of the PIE-LTER marshes during summer 2016. The goal was to assess whether pond metaoblism rates varied predictably with pond dimensions (e.g., surface area, volume) or geographic attributes (e.g., elevation, distance from upland, marsh region). Sensors recording dissolved oxygen (DO), temperature, and salinity were deployed at mid-depth and rotated between the six ponds through the June - August study period. Metaoblism rates were calcluated based on a free-water diel oxygen approach.
Campus Pond (Buffalo Creek Watershed) Water Data from 2021-11-03 to 2021-11-23
<pre># General Metadata for Campus Pond Sampling Station ## Files Specific metadata for each deployment and sensor can be found as text files with the file format of: LP_CampusPond_DO_YYYY-MM-DD_metadata.txt LP_CampusPond_Depth_YYYY-MM-DD_metadata.txt LP_CampusPond_CT_YYYY-MM-DD_metadata.txt Where YYYY-MM-DD is the date that the sampling period ended. NOTE: The metadata in the above file is collected from the data logger and does not have all of fields present in the final data set, because some were created during data cleaning. Details on how the data were cleaned and variables created can be found at in the cleaning scripts on Gitlab [https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts](https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts). ## File Created * 2021-11-10 by KF - copied and modified from HS_wetland_general_metadata.md ## File Modified ## Description These data are from the sampling station in Campus Pond on the Longwood University Campus. The sensors are along the S shoreline of the pond (37.296813, -78.397702). All data are CC-BY and should be cited using the DOI available at https://zenodo.org/communities/leo/ ## Station Specifics The specific sensors at the site are: * Water Temperature (dC) and Dissolved Oxygen (mg/l) are collected with a Onset HOBO U26-001 Dissolved Oxygen Logger * Water Temperature (dC) and Water Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger * Water Temperature (dC) and Conductivity are collected with an Onset HOBO U24-001 Conductivity Logger * Air Temperature (dC) and Barometric Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger mounted in the air next to the wetland. The sensors are sampled every 15 minutes ## Measurement Parameters, units, and Variable Names * date.time - the date and time that the record was collected, reported in POSIX standard time (YYYY-MM-DD HH:MM:SS) * observation.DO, .CT, .press, or .BP - the incremental number of each observation from the DO, conductivity, water pressure, or barometric pressure sensor. * timestamp.DO, .CT, .press, or .BP - the data and time that the record was collected, as reported by the data logger (MM/DD/YY HH:MM:SS A/PM) from the DO, conductivity, water pressure, or barometric pressure sensor. * DO - the concentration of dissolved oxygen in the water (mg/L) * Temp.DO, .CT, .press, or .BP - the temperature (dC) from the DO, conductivity, water pressure, or barometric pressure sensor. * Pressure.press or .BP - the pressure recorded by the pressure transducer (kPa) on the water pressure or barometric pressure sensor. * Z - the depth of the water (cm). * Low_Range_CT - the conductivity read from 0 - 2500 uS/cm (uS/cm) * Full_Range_CT - the conductivity read from 0 - 15000 uS/cm (mmHg) * press.g.cm2 - the pressure from the water pressure sensor (g/cm^2) * BP.g.cm2 - the barometric pressure from the barometric pressure sensor (g/cm^2) </pre>
Campus Pond (Buffalo Creek Watershed) Water Data from 2022-02-17 to 2022-03-14
<p>General Metadata for Campus Pond Sampling Station</p> <p>Files</p> <p>Specific metadata for each deployment and sensor can be found as text files with the file format of:</p> <pre><code>LP_CampusPond_DO_YYYY-MM-DD_metadata.txt LP_CampusPond_Depth_YYYY-MM-DD_metadata.txt LP_CampusPond_CT_YYYY-MM-DD_metadata.txt</code></pre> <p>Where YYYY-MM-DD is the date that the sampling period ended.</p> <p>NOTE: The metadata in the above file is collected from the data logger and does not have all of fields present in the final data set, because some were created during data cleaning. Details on how the data were cleaned and variables created can be found at in the cleaning scripts on Gitlab <a href="https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts">https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts</a>.</p> <p>File Created</p> <ul> <li>2021-11-10 by KF - copied and modified from HS_wetland_general_metadata.md</li> </ul> <p>File Modified</p> <p>Description</p> <p>These data are from the sampling station in Campus Pond on the Longwood University Campus. The sensors are along the S shoreline of the pond (37.296813, -78.397702).</p> <p>All data are CC-BY and should be cited using the DOI available at <a href="https://zenodo.org/communities/leo/">https://zenodo.org/communities/leo/</a></p> <p>Station Specifics</p> <p>The specific sensors at the site are:</p> <pre><code>* Water Temperature (dC) and Dissolved Oxygen (mg/l) are collected with a Onset HOBO U26-001 Dissolved Oxygen Logger * Water Temperature (dC) and Water Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger * Water Temperature (dC) and Conductivity are collected with an Onset HOBO U24-001 Conductivity Logger * Air Temperature (dC) and Barometric Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger mounted in the air next to the wetland.</code></pre> <p>The sensors are sampled every 15 minutes</p> <p>Measurement Parameters, units, and Variable Names</p> <pre><code>* date.time - the date and time that the record was collected, reported in POSIX standard time (YYYY-MM-DD HH:MM:SS) * observation.DO, .CT, .press, or .BP - the incremental number of each observation from the DO, conductivity, water pressure, or barometric pressure sensor. * timestamp.DO, .CT, .press, or .BP - the data and time that the record was collected, as reported by the data logger (MM/DD/YY HH:MM:SS A/PM) from the DO, conductivity, water pressure, or barometric pressure sensor. * DO - the concentration of dissolved oxygen in the water (mg/L) * Temp.DO, .CT, .press, or .BP - the temperature (dC) from the DO, conductivity, water pressure, or barometric pressure sensor. * Pressure.press or .BP - the pressure recorded by the pressure transducer (kPa) on the water pressure or barometric pressure sensor. * Z - the depth of the water (cm). * Low_Range_CT - the conductivity read from 0 - 2500 uS/cm (uS/cm) * Full_Range_CT - the conductivity read from 0 - 15000 uS/cm (mmHg) * press.g.cm2 - the pressure from the water pressure sensor (g/cm^2) * BP.g.cm2 - the barometric pressure from the barometric pressure sensor (g/cm^2)</code></pre>
Fig 2 in Monitoring and assessing the physico-chemical water properties and planktonic communities in tilapia nursing pond
Fig 2: Percentages of different phytoplankton communities during the study period (a, b c, are indicating the size category as small, medium and large)
Fig 1 in Monitoring and assessing the physico-chemical water properties and planktonic communities in tilapia nursing pond
Fig 1: Percentages of total phytoplankton and total zooplankton in all size categorized pond during the sampling period
Fig 2 in Water quality, yield and cost-benefit analysis of rain water ponds of Cuttack district: A comparison between Indian major carp and GIFT Tilapia
Fig 2: Average share of various cost in IMC poly-culture and GIFT mono-sex culture in T1 & T2 (2018-19)
Fig 5 in Species Diversity Of Wetland Birds, Depending On Area, Overgrowth Of Water Bodies On The Example Of Sovskie Ponds (Ukraine)
Fig 5. Percentage of species under conditions of overgrowth of a reservoir with macrophytes, a - 5% overgrowth, b - 90% overgrowth, c - 45% overgrowth, d - 55% overgrowth, e - 65% overgrowth.
Fig. 2 in Not only pond sliders: freshwater turtles in the water bodies of the Milan northern urban area (Italy)
Fig. 2 - Distribution maps of the species found in the study area. Circled letters: species records; when the position is approximated, the circle is dashed. P. subrufa records are omitted because the species was recovered far from the wetlands; also T. scripta is not shown, because the species was excluded from the study. Letters indicate the wetlands as in Fig. 1 (modified from https://d-maps.com/ and GeoPortale Regione Lombardia). / Mappa di distribuzione delle specie rinvenute nell'area di studio. Lettera cerchiata: specie presente; quando la posizione è approssimativa, il cerchio è tratteggiato. Il dato per P. subrufa è omesso in quanto la specie è stata rinvenuta lontano dalle zone umide; la distribuzione di T. scripta non è indicata poiché la specie non è oggetto del presente studio. Le aree umide sono indicate da lettere secondo la nomenclatura usata in Fig. 1 (modificato da https://d-maps.com/ e GeoPortale Regione Lombardia).
Fig. 1 in Not only pond sliders: freshwater turtles in the water bodies of the Milan northern urban area (Italy)
Fig. 1 - Study area (Lombardy region, Northern Italy). Letters indicate each studied wetland (modified from www.d-maps.com and GeoPortale Regione Lombardia). / Area di studio (Lombardia, Italia Settentrionale). Ogni lettera identifica un'area umida indagata (modificato da https://d-maps.com/ e GeoPortale Regione Lombardia).
Figure 3 in Water quality assessment in an irrigation pond based on adult caddisfly (Insecta: Trichoptera) assemblages
Figure 3. Canonical Correspondence Analysis (CCA) showing correlation between caddisflies species and physicochemical variables. Abbreviations for taxonomy are shown in Table 2.
Figure 2 in Water quality assessment in an irrigation pond based on adult caddisfly (Insecta: Trichoptera) assemblages
Figure 2. The total number of species and individuals caught at an irrigation pond in the Kasetsart University, Thailand.
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.
Cone Pond, Thornton, NH water chemistry
Cone Pond is an acidic pond on the White Mountain National Forest, NH, USA that was monitored for several decades to investigate the ecology of an acidic aquatic ecosystem and to document impacts of acid deposition. This dataset includes chemical analyses of water samples collected at Cone Pond from 1988 to 2013.
PIE LTER diel surface water chemistry of two high marsh ponds, Rowley, MA, during the summer of 2016.
We measured diel fluctuations in surface water chemistry of two high marsh ponds in July 2016. The ponds are shallow and experience day-night swings in oxygen concentrations, from super-saturation to anoxia. Our goal was to characterize changes in geochemical properties and dissolved organic carbon concentrations that accompany wide swings in oxygen concentrations. These data provide information about the responsiveness of microbial communities and how the dominance of redox-sensitive metabolisms changes over short time scales (e.g., hours) to feed back on pond water chemistry.
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