Find research datasets worth reusing

openCC (other)Nov 2025View details →

Surface Water Quality Monitoring Data collected in South Florida Coastal Waters (FCE LTER), Florida, USA, June 1989-ongoing

The Southeast Environmental Research Center at Florida International University operates a network of 331 fixed sampling sites distributed throughout the estuarine and coastal ecosystems of south Florida. The purpose of this network is to address concerns in regional water quality which cross and overlap separate political boundaries. Funding has come from different sources with individual programs being added as funding became available. Biscayne Bay, Florida Bay, Whitewater Bay, Ten Thousand Islands, Rookery Bay, Estero Bay, and Pine Island Sound are sampled monthly while the Florida Keys National Marine Sanctuary (FKNMS) and the southwest shelf are sampled quarterly. Variables currently being measured include surface and bottom temperature, salinity, dissolved oxygen, nitrate, nitrite, ammonium, total nitrogen, total organic nitrogen, total phosphorus, soluble reactive phosphorus, total organic carbon, total silicate, chlorophyll a, alkaline phosphatase activity, turbidity, and light extinction. The purpose of this network is to address concerns in regional water quality which cross and overlap separate political boundaries. One of the products is a quasi-synoptic big picture of nutrient and phytoplankton biomass distributions over the South Florida Coastal Waters. The SERC network will, in time, provide us with the data necessary to determine whether conditions within the estuaries and sanctuary are improving or declining.

openCC (other)May 2025View details →

Water Depths and Water Temperatures near Soil Surface from Shark River Slough, Everglades National Park (FCE LTER), Florida, USA, October 2000 - ongoing

Water depth (from October 2000 to present) and water temperature (from September 2021 to present) are recorded at least hourly at SRS1c (not active), SRS1d, SRS2, SRS3, SRS4, SRS5, and SRS6. Water depth is measured with pressure water level loggers (Infinities USA or HOBO) that record water height relative to the local soil surface. Water temperature near soil surface is measured with HOBO loggers. Note by IM (2021): The water meters at some of the SRS sites have been moved over the years as boardwalks have been reconstructed. There is no set survey datum for these sites, so it is impossible to correct the data to an actual datum. For hydrologic applications, it may be better to use water level data from USGS stations.

openCC (other)Dec 2025View details →

Water Depths and Water Temperatures near Soil Surface from Taylor Slough, Everglades National Park (FCE LTER), Florida, USA, August 1999 - ongoing

Water depth (from August 1999 to present) and water temperature (from May 2021 to present) are recorded hourly at TS/Ph1a, TS/Ph2 and TS/Ph3 and every 30 minutes at TS/Ph6a and TS/Ph7a. Water depth is measured with pressure water level loggers (Infinities USA or HOBO) that record water height relative to the local soil surface. Water temperature near soil surface is measured with HOBO loggers. Note by IM (2021): The water meters at some of the TS sites have been moved over the years as boardwalks have been reconstructed. There is no set survey datum for these sites, so it is impossible to correct the data to an actual datum. For hydrologic applications, it may be better to use water level data from USGS stations.

openCC (other)Nov 2022View details →

Globally distributed lake surface water temperatures collected in situ and by satellites; 1985-2009

Global environmental change has influenced lake surface temperatures, a key driver of ecosystem structure and function. Recent studies have suggested significant warming of water temperatures in individual lakes across many different regions around the world. However, the spatial and temporal coherence associated with the magnitude of these trends remains unclear. Thus, a global dataset of water temperature is required to understand and synthesize global, long-term trends in surface water temperatures of inland bodies of water. We assembled a database of summer lake surface temperatures for 291 lakes collected in situ and/or by satellites for the period 1985-2009. In addition, corresponding climatic drivers (air temperatures, solar radiation, and cloud cover) and geomorphometric characteristics (latitude, longitude, elevation, lake surface area, maximum depth, mean depth, and volume) that influence lake surface temperatures were compiled for each lake. This unique dataset offers an invaluable baseline perspective on global-scale lake thermal conditions as environmental change continues. This dataset accompanies a data publication in the journal Scientific Data

openCC (other)Jun 2025View details →

SBC LTER: Reference: Sea-surface water temperature, Santa Barbara Harbor, Santa Barbara, CA, USA, 1955 to present, ongoing

The SBC-LTER has access to data on seawater temperature collected at Santa Barbara Harbor, Santa Barbara, CA, USA through the Scripps Institution of Oceanography Manual Shore Stations program. The SIO Manual Shore Stations program provides data and information about this shore station. For further information, please visit the SIO Manual Shore Stations website at https://library.ucsd.edu/dc/object/bb07606686. Please note: manual shore station data is updated periodically, not continuously. Funding for the Shore Stations Program provided by the California Department of Parks and Recreation, Natural Resources Division, Award# C22820005. Contact shorestation@ucsd.edu if you have questions

opencc-by-4.0Oct 2023View details →

GRWSE-global river water surface elevation from sentinel-3

This dataset includes time series of Water Surface Elevation (WSE) of large rivers at over 3000 virtual stations. The WSE time series were created using Sentinel-3A and Sentinel-3B altimetry data.

opencc-by-sa-4.0Sep 2018View details →

Landsat bands (cloud free), tree cover (2000, 2010), bare-ground and surface water occurrence at 250 m based on GlobalForestWatch and USGS

Landsat bands (cloud free) and tree cover (2000) based on Hansen et al. (2013), global surface water occurrence based on Pekel at al. (2016), and tree cover and bare-ground cover (2010) based the USGS land cover mapping projects (University of Maryland, Department of Geographical Sciences and USGS). All layers resampled to spatial resolution 1/480 d.d. (about 250 m) using gdalwarp with "average" resampling. Antarctica is not included. Original layers are available at 30 m resolution. If you discover a bug, artifact or inconsistency in the maps, or if you have a question please use some of the following channels: <ul> <li>Technical issues and questions about the code: <a href="https://gitlab.com/openlandmap/global-layers/issues">https://gitlab.com/openlandmap/global-layers/issues</a> </li> <li>General questions and comments: <a href="https://disqus.com/home/forums/landgis/">https://disqus.com/home/forums/landgis/</a></li> </ul> All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention: <ul> <li>lcv = theme: land cover,</li> <li>bareground = variable: occurrence of bareground,</li> <li>landsat.usgs = determination method: Landsat landcover at 30 m resolution project (https://landcover.usgs.gov/glc/),</li> <li>p = probability or fraction,</li> <li>250m = spatial resolution / block support: 250 m,</li> <li>s0..0cm = vertical reference: land surface,</li> <li>2010..2010 = time reference: year 2010,</li> <li>v1.0 = version number: 1.0,</li> </ul>

opencc-by-4.0Aug 2019View details →

Table S27: Target and identified unknown organic micropollutants detected in surface water samples taken during heavy rain events

In the following table, peak intensities of detected organic micropollutants in water samples are displayed. This data table is part of the appendix of Chapter 4 of the PhD thesis “Novel approaches to identify drivers of chemical stress in small rivers” by Liza-Marie Beckers prepared at RWTH Aachen University and at the Helmholtz Centre for Environmental Research-UFZ. In Chapter 4, precipitation-related pollutant patterns and indicator compounds during heavy rain events were identified in the Holtemme River by nontarget screening and cluster analysis. The table contains peak heights of organic micropollutants detected in water samples taken during heavy rain events in the Holtemme River (Saxony – Anhalt, Germany). The table is structured into the following columns: Compound name, use class of compound (e.g., pharmaceutical or pesticide), distinction between target or identified unknown compounds, mass-to-charge ratio (m/z), retention time (RT), assignment to a pattern identified by cluster analysis (i.e., “Base” or “Quick”), the probability of belonging to the assigned pattern as number between 0 and 1 as well as the peak height of the compound in each sample. The samples are indicated by "B" for "bottle" and a number from 1-16. The use class “NA” indicates that now major use class for this compound could be identified. The sampling was triggered by combined sewer overflow at a wastewater treatment plant upstream of the sampling point. Samples were taken by an automated sampler in 30-min composite samples for 8 hours resulting in 16 samples per rain event. In total, 6 heavy rain events from May to September 2016 were sampled during this study. The table is divided into 6 subtables (i.e., Table S27 A-F). Each subtable displays compounds and their peak heights detected in samples from one heavy rain event. The different rain events are abbreviated by the sampling date: Table S27A displays results from the rain event samples May 29th 2016 : E2905 Table S27B displays results from the rain event samples June 01st 2016 : E0106 Table S27C displays results from the rain event samples June 24th 2016 : E1306 Table S27D displays results from the rain event samples June 13th 2016 : E2406 Table S27E displays results from the rain event samples July 13th 2016 : E1307 Table S27F displays results from the rain event samples September 17th 2016 : E1709 Chemical analysis of the water samples was performed by liquid chromatography (UltiMate 3000 LC system (Thermo Scientific)) coupled to high resolution mass spectrometry (Q Exactive Plus, Thermo Scientific) with a heated electrospray ionization (HESI) source. Nontarget screening was performed as it allows for a comprehensive characterization of the chemical exposure during heavy rain events. However, only annotated target compounds and unknown compounds identified by structure elucidation are presented in the table. Details on data evaluation methods are described in Chapter 4 of the PhD thesis. Beckers, L.M. (2019): Novel approaches to identify drivers of chemical stress in small rivers. RWTH Aachen University, Aachen.

opencc-by-4.0Dec 2018View details →

Surface water and flooding dynamics based on seasonally continuous Landsat data (1986-2011) in a dryland river basin (monthly, seasonally, and yearly animations)

The animations provided here are part of the following publication: Tulbure, M.G. and M. Broich (2018). Spatiotemporal patterns and effects of climate and land use on surface water extent dynamics in a dryland region with three decades of Landsat satellite data. Science of the Total Environment. https://www.sciencedirect.com/science/article/pii/S0048969718347466 Please refer to the above mentioned publication for a description of the data and interpretation of the patterns. The animations are based on statistically validated surface water and flooding extent dynamics data derived from seasonally continous Landsat TM/ETM+ and random forest models from 1986 to 2011 over Australia's Murray-Darling Basin. The overall accuracy was over 99% and producer's accuracy for water 87% +/- 3%.  The method is described in the following publication:  Tulbure, M.G., M. Broich, S.V. Stehman, A. Kommareddy. (2016). Surface water extent dynamics from three decades of seasonally continuous Landsat time series at subcontinental scale in a semi-arid region. Remote Sensing of Environment. 178: 142-157 and available here: https://www.sciencedirect.com/science/article/pii/S0034425716300621

opencc-by-4.0Jan 2023View details →

Water stable isotope, temperature and electrical conductivity dataset (snow, ice, rain, surface water, groundwater) from a high alpine catchment (2019-2021).

Data collected in the Otemma forefield in Switzerland (45°56’03”N,7°24’42”) from July 2019 to October 2021. Data were collected by the research teams of Bettina Schaefli2 and Stuart N. Lane1. 1 Institute of Earth Surface Dynamics (IDYST), University of Lausanne, 1015 Lausanne, Switzerland 2 Institute of Geography (GIUB), University of Bern, 3012 Bern, Switzerland For further information, please contact: <ul> <li>tom.muller.1@unil.ch</li> </ul> Description of the dataset This dataset contains water stable isotope (δ2H, δ17O, δ18O), water temperature and water electrical conductivity (EC) measurements collected from the Otemma glacier catchment. All water isotope samples were collected directly from the source and stored in 12 mL amber glass vials with an air-tight caps. River samples were first collected with an automatic ISCO 6712 portable water sampler with 1L open plastic bottles and transferred in 12 mL vials every one to two weeks. All isotope analysis were performed using a Wavelength-Scanned Cavity Ring Down Spectrometer (Picarro 2140-I, Santa Clara, California, USA) and expressed relative to the international Vienna Standard Mean Ocean Water (VSMOW) standards. All EC and water temperature measurements were performed with a WTW Multi 3510 IDS logger with a IDS TetraCon® 925 probe. The dataset contains measurements performed at various locations within the catchment. A total of approximately 1500 measurements are provided. In the dataset each point correspond to a measurement station (column "Station") which we classified in specific class of water (column "Type") as follows : <ul> <li>Stream : samples collected at three locations, from the glacier snout, after a small outwash plain and 2km downstream.</li> <li>Tributary : 5 hillslopes tributaries originating from small seasonal overland flow or small springs at the base of the morainic hillslope. Those tributaries were monitored weekly. In addition, a few other seasonal lateral streams were sampled in various locations (Type: Other tributaries).</li> <li>Bedrock : A few exfiltrations directly leaking out of the bedrock outcrop were sampled.</li> <li>Ice : Ice was sampled either as surface ice (small cores 5 cm deep), as deeper cores (5 to 8m deep) or as meltwater from supraglacial gullies. All solid ice samples were melted at ambiant air temperature in air-tight plastic bags before being transferred into 12 mL vials.</li> <li>Snow : The snowpack was sampled either at the surface (0 to 5cm) or at about 20 cm depth. Where possible, meltwater leaking from the snowpack was sampled. At 3 locations in 2021, we dug snowpits from which we sampled snow at different layers with depth. All solid snow samples were melted at ambiant air temperature in air-tight plastic bags before being transferred into 12 mL vials</li> <li>Rain : Rainwater was mostly sampled at our camp site at 2450 m. asl. Rainwater samples represent single rain events which are identified by dry periods of at least one day long.</li> <li>Groundwater : shallow (2 to 3 meters) fully-screened groundwater wells were installed in the outwash plain and water sampled monthly in the snow-free season.</li> </ul> - GPS coordinates are provided with each point (Swiss coordinate system CH1903+ / LV95  (EPSG: 2056)). - Dates are provided in local timezone (GMT+1 with daylight saving time) and in UTC date format. - Analyitcal error from the Picarro spectrometer is reported as 1 standard deviation. More information can be accessed in the corresponding publication by Müller et al. (to be published in 2023). Data files <ul> <li>Otemma_isotope_EC_T_2019_2021.csv : file containing all data with GPS coordinates</li> <li> isotope_locations_Otemma.jpg : an overview of the locations of each measurement point </li> <li> Otemma_Isotopes_2019-2020.html : interactive plots of all datasets (δ2H, EC, temperature), classified by Type. </li> </ul>

opencc-by-4.0May 2023View details →

HYPSTAR hyperspectral water reflectance and derived water quality products (suspended particulate matter and chlorophyll-a concentration) at the Blankaart surface water reservoir (BE)

Hyperspectral Water Leaving Reflectance spectra (2988) measured between 2021-02-03 and 2022-08-03 at the Blankaart Surface Water Reservoir (Belgium, 50.98857N, 2.835213E) with the HYPSTAR® (ID: HYPSTAR_12120241). Detailed description of the data collection, processing and analysis can be found in Goyens et al.- Remote Sens. 2022 - 14(21)- 5607; https://doi.org/10.3390/rs14215607. <ol> <li>HYPSTAR_W_BSBE_L2A_REFL_20210203_20220803_v1.csv</li> </ol> Chlorophyll-a (Chl-a) concentration and Suspended Particulate Matter (SPM) were derived from the above dataset of hyperspectral water reflectance and estimated according to different algorithms found in the litterature, i.e., <ol> <li>HYPSTAR_W_BSBE_CHLA_SIMIS_20210203_20220803_v1.csv: Chlorophyll-a concentration estimated from the HYPSTAR® reflectance measurements and following the algorithm suggested by Simis et al. (2005; https://doi.org/10.4319/lo.2005.50.1.0237) with a variable absorption coefficient of phytoplankton per unit of Chl-a concentration as described in Goyens et al. (2022)</li> <li>HYPSTAR_W_BSBE_CHLA_CRAT_20210203_20220803_v1.csv: Chlorophyll-a concentration estimated with the HYPSTAR® reflectance measurements and following the algorithm suggested by Ruddick et al. (2001; https://doi.org/10.1364/AO.40.003575.) with a variable absorption coefficient of phytoplankton per unit of Chl-a concentration as described in Goyens et al. (2022)</li> <li>HYPSTAR_W_BSBE_SPM_20210203_20220803_v1.csv: Suspended particulate matter estimated with the HYPSTAR® reflectance measurements and following the algorithm suggested by Nechad et al. (2010) at 700 nm</li> </ol>

opencc-by-4.0Jul 2023View details →

Evaluation of a wind tunnel designed to investigate the response of evaporation to changes in the incoming longwave radiation at a water surface

Experimental Record of a Longwave-Evaporation experiment. The record to be referenced in a forthcoming scientific paper.

openCC (other)Aug 2022View details →

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.

openCC (other)Oct 2023View details →

Historical and future Lake Surface Water Temperature for 80 major lakes in Southeast Asia [LSWT-SEA]

The present dataset is part of a study delving into the intricate relationship between lake surface temperature (LSWT) and the broader context of climate change in the ecologically diverse region of Southeast Asia (SEA). Recognizing LSWT as a highly responsive indicator of climatic shifts, the research aims to shed light on the region's vulnerability to these changes. Using a suite of predictive models (namely Multilinear Regression (MLR), Multilayer perceptron (MLP), Random Forest (RF), eXtreme Gradient Boosting (XGB), Multilayer perceptron (MLP)) the study reconstructs historical LSWT trends from 1986 to 2020 and projects future scenarios until 2100, contingent upon various Representative Concentration Pathway (RCP) trajectories. Using MODIS-derived LSWT as predicted variable. The dataset package includes the data used to carry out the research: ECMWF ERA5 and CHIRPS climatic predicting variables, MODIS-derived daytime and nighttime LSWT, historically predicted daily daytime and nighttime LSWT, future predictions of LSWT for multiple Representative Concentration Pathways (RCPs), long term historical and future trends.

openCC (other)Nov 2019View details →

Summer high frequency measurements of dissolved O2 and CO2 concentrations and water temperature at the surface of 11 northern lakes

This dataset includes high frequency paired measurements of dissolved O2 and CO2 concentrations at the surface (0.5 to 2 m depth) of 11 lakes in the Northern Hemisphere. Measurements were taken every 2 hours in summer (July and August) of various years depending on lakes (between 2011 and 2014). The dataset is used to test a conceptual framework on the controls of coupling and decoupling of these two gases. In all lakes dissolved CO2 was measured with infrared analyzer coupled with a diffusion membrane and dissolved O2 with optodes. All gas measurements are paired with water temperature provided by one of the gas probe (usually from the O2 probe).

openCC0Sep 2020View details →

Nyack Floodplain RiverNet surface water and groundwater dissolved oxygen, conductivity, water level, and temperature Northwest Montana, USA, 2012-2020

Water dissolved oxygen, conductivity, temperature, and level from ten locations in the Nyack Floodplain of the Middle Fork of the Flathead River in Northwest Montana, USA. Measurements are made hourly for the period of 2012 to 2020. Six sensor are placed in groundwater wells and four are placed in surface water. Data up to June 26h, 2019 have been cleaned to remove bad data and flag potentially anomalous observations.

openCC (other)Jul 2021View details →

LAGOS-US NETWORKS v1.0: Data module of surface water networks characterizing connections among lakes, streams, and rivers in the conterminous U.S

Knowing the degree of surface water connectivity among aquatic ecosystems can help scientists better understand and predict the movement of materials and biota across ecosystems. Methods to quantify surface water networks that include lake and stream connections at broad spatial scales are rare because it is difficult to balance accurate estimates of surface water connectivity and computational challenges. The LAGOS-US NETWORKS (NETS) module contains surface connectivity metrics for lake networks across the conterminous United States. We applied a graph theory approach to identify lake networks (i.e. a set of lakes connected by streams either upstream, downstream, or both) created from the medium resolution NHD lakes, streams, and rivers and subsequently derive surface water connectivity metrics for lakes and networks. Using this approach, we created a total of 898 networks that include 86,511 lakes. The NETS module includes a table with metrics for connections between lakes (both upstream and downstream), dams, network position, and whole networks. NETS also includes a flow table and bidirectional and unidirectional distance tables that provide the distances between every pair of connected lakes.

openOpenJan 2013View details →

Surface carbon, water and energy fluxes measured by eddy covariance at 3 sites within the Alaska Peatlands Experiment and Bonanza Creek Experimental Forest

These data are simultaneous and continuous measurements of carbon, water and energy fluxes of the terrestrial landscape. These fluxes are major regulatory drivers of the boreal climate system and form key linkages and feedbacks between the land surface, the atmosphere and the oceans. At the APEX project site, within Bonanza Creek Experimental Forest, this monitoring is repeated across a chronosequence of permafrost degradation; the Black Spruce site is an area of stable permafrost with intact black spruce forest (APEX gamma site), the Thermokarst site is an active thermokarst zone with considerable tree mortality (APEX betaSW site), the Fen site is within a stable treeless fen with deep active layer depth (APEX apexcon,low, and ele sites). The main variables being monitored are the instananeous fluxes of CO2, water vapor and surface energy (shortwave, longwave and net radiation), secondary variables included photosynthetically active radiation (PAR), air and soil temperatures, rainfall, snow depth, soil moisture content, wind direction and speed, and average atmospheric concentrations of CO2 and H2O through the year.

openCC (other)Oct 2025View details →

Abiotic monitoring of physical characteristics in porewaters and surface waters of mangrove forests from the Shark River Slough and Taylor Slough, Everglades National Park (FCE LTER), South Florida, USA, December 2000 - ongoing

Data on porewater salinity, temperature, conductivity, pH and redox have been collected to help explain patterns found in porewater nutrient concentrations that were sampled in the same plots. See knb-lter-fce.1171 (https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-fce&identifier=1171) for related porewater-nutrient-concentration data.