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20 results for “Lake Database”
LAGOS-NE-LIMNO v1.087.3: 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: 1925-2013
This data package, LAGOS-NE-LIMNO v1.087.3, is 1 of 5 data packages associated with the LAGOS-NE database-- the LAke multi-scaled GeOSpatial and temporal database. With this release, only this data package is being updated and users are expected to use prior releases of the other types of data. Please see the attached additional documentation for a full description of the changes that have been made for this new release.The data packages that make up LAGOS-NE include the following information on lakes and reservoirs in 17 lake-rich states in the Northeastern and upper Midwestern U.S. (1) LAGOS-NE-LOCUS v1.01: lake location and physical characteristics for all lakes greater than one hectare. (2) LAGOS-NE-GEO v1.05: ecological context (i.e., the land use, geologic, climatic, and hydrologic setting of lakes) for all lakes and for all spatial resolutions, also called ‘zones’ (i.e., ecoregions, states, counties). These geospatial data were created by processing national-scale and publicly-accessible datasets to quantify numerous metrics at multiple spatial resolutions. (3) LAGOS-NE-LIMNO v1.087.3: 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. This module includes variables that are most commonly measured by state agencies and researchers for studying eutrophication. For each water quality data value, we also include metadata related to the sampling program, methods, qualifiers with data flags from the original program (qual, not standardized for LAGOS-NE), censor codes from our quality control procedures (censorcode, standardized for LAGOS-NE), and the date of each sample. (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-N
Wisconsin Lake Plants - multi source database of lake plant abundance 1930 - 2004
This data set provides sampling-point by sampling-point macrophyte data for lakes sampled by a number of agencies in Wisconsin. The relational tables in this dataset were originally used to generate plant community tables. This dataset contains detailed and recent data from approximately the 1970s onward. Sampling timing and intensity varied. Table DATSOUR contains sources of data for tables AQUAPLT2 and LAKEHAB. Table AQUAPLT2 gives an estimate of plant density at each sample point. Table MAXDEPLNG has initial lake parameters derived from data in AQUAPLT2 and LAKEHAB Table LAKEHAB contains habitat characteristics at macrophyte sampling locations. Table PLTNAME has species information for plants in tables AQUAPLT2 and LAKESPEC. Table LAKES contains information for lakes included in this dataset. Table COUNTY contains information associated with the counties where the lakes in the AQUAPLT2 dataset and the LAKESPEC dataset are located. . Sampling Frequency: varies Number of sites: 1938
HarP: Harmonized Prior river-lake database
<p><strong>Contact</strong>: Md Safat Sikder (mssikder@illinois.edu), Jida Wang (jidaw@illinois.edu)</p> <p> </p> <p><strong>Citation</strong></p> <p>Sikder, M. S., Wang, J., Allen, G. H., Sheng, Y., Yamazaki, D., Crétaux, J.-F., and Pavelsky, T. M., 2024. HarP: Harmonized Prior river-lake database. <em>Zenodo</em>, <a href="https://doi.org/10.5281/zenodo.14205131">https://doi.org/10.5281/zenodo.14205131</a>.</p> <p>If you only use the PLD-TopoCat dataset, please cite the following paper:</p> <p>Sikder, M. S., Wang, J., Allen, G. H., Sheng, Y., Yamazaki, D., Song, C., Ding, M., Crétaux, J.-F., and Pavelsky, T. M., 2023. Lake-TopoCat: A global lake drainage topology and catchment dataset. <em>Earth System Science Data</em>, 15, 3483-3511, <a href="https://doi.org/10.5194/essd-15-3483-2023">https://doi.org/10.5194/essd-15-3483-2023</a>.</p> <p> </p> <p><strong>Data description and components</strong></p> <p><strong>The Harmonized Prior river-lake database (HarP) for SWOT</strong> integrated the SWOT River Database (SWORD) (<em>Altenau et al.</em>, 2021) and the SWOT Prior Lake Database (PLD) (<em>Wang et al.</em>, 2023) into <strong>a geometrically (lake/river) explicit but topologically harmonized vector database</strong> to allow for coupled fluvial-lacustrine applications, including a synergistic use of both river and lake products from SWOT. </p> <p>In addition to the input river network (SWORD v16) and lake database (PLD v106), we used the MERIT Hydro v1.0.1 (<em>Yamazaki et al.</em>, 2019), a high-resolution (~90 m) global hydrography dataset, to develop this database.</p> <p>The SWORD-PLD harmonization process involves three major steps, with Step 3 being divided into three sub-steps. The processing chain is illustrated in the attached Figure "<em>SWORD-PLD_harmonization_steps.jpg</em>", as well as in Section 2 of the product description document. The HarP database consists of the outputs from each of the steps. For convenience, the global landmass (excluding Antarctica) was partitioned to 68 Pfafstetter Level-2 basins/regions, with their IDs shown in Figure "<em>Pfaf2_basins.jpg</em>" attached.</p> <p> </p> <p>The HarP database consists of five datasets or components (outputs from each step), each with multiple features. The five datasets are described below, and more details are elaborated in the product description document.</p> <p><strong>1. Harmonized SWORD-PLD </strong>(file name "<em>Harmonized_SWORD_PLD</em>"): This is the fully harmonized SWORD-PLD dataset, <strong>the primary product of HarP </strong>(i.e., output of Step 3.3 in Figure "<em>SWORD-PLD_harmonization_steps.jpg</em>"). This dataset couples SWORD and PLD into a geometrically segmented but topologically integrated dataset at the node, reach, and catchment scales (stored by three feature layers, respectively): </p> <p> (a) Harmonized feature nodes: Harmonized_feature_nodes_pfaf_xx<br> (b) Harmonized river network: Harmonized_river_network_pfaf_xx<br> (c) Harmonized feature catchments: Harmonized_feature_catchments_pfaf_xx<br> Note: ''pfaf_xx'' indicates the Pfafstetter Level-2 basin ID (shown in Fig. 'Pfaf2_basins.jpg').</p> <p>Figure "<em>HarP_example.jpg</em>", attached to this database, is an example of the fully harmonized SWORD-PLD dataset for the Ohio River Basin. The example shows three main features of the dataset: feature nodes (i.e., reach downstream ends, lake inlets, and lake outlets; see Fig. 3 in the product description document for definitions), river reaches (i.e., reaches characterized by SWORD alone, characterized by TopoCat alone, and shared by both SWORD and TopoCat), and catchments segmented by each of the feature nodes.</p> <p><strong>2. Intersected SWORD-PLD drainage configuration </strong>(file name "<em>Intersected_SWORD_PLD</em>"): This dataset is the intersected SWORD-PLD (prior river-lake) features (i.e., output of Step 2 in Figure "<em>SWORD-PLD_harmonization_steps.jpg</em>"). This dataset was constructed independently from Step 1 and Step 3. In this dataset, the original geometries of SWORD and PLD are not altered, but instead, their geometric and drainage topological relationships are configured in the attribute tables. This dataset consists of three features:</p> <p> (a) Intersected reaches: Intersected_SWORD_reaches_pfaf_xx<br> (b) Intersected nodes: Intersected_SWORD_nodes_pfaf_xx<br> (c) Intersected lakes: Intersected_PLD_lakes_pfaf_xx</p> <p><strong>3. PLD-TopoCat </strong>(file name "<em>PLD_TopoCat</em>"): This dataset is the lake drainage topology and catchments (TopoCat) for PLD lakes (i.e., output of Step 1 in Figure "<em>SWORD-PLD_harmonization_steps.jpg</em>"). PLD-TopoCat was developed to generate detailed lake drainage topology and connecting paths, which were later used to configure the off-SWORD-network PLD lakes into the tributaries that drain to SWORD. PLD-TopoCat was generated from PLD v106 and MERIT Hydro. Details of the developiong process and algorithm for TopoCat can be found at Sikder at al., (2023). PLD-TopoCat dataset contains six features:</p> <p> (a) Lake original polygon: PLD_lakes_pfaf_xx<br> (b) Lake raster polygon: Lake_raster_polygons_pfaf_xx<br> (c) Lake outlets: Lake_outlets_pfaf_xx<br> (d) Lake catchments: Lake_catchments_pfaf_xx<br> (e) Inter-lake reaches: Inter_lake_reaches_pfaf_xx<br> (f) Lake-network basins: Lake_network_basins_pfaf_xx<br> Note: full version of the PLD-TopoCat is available <a href="https://doi.org/10.5281/zenodo.14202301">here</a>.</p> <p><strong>4. SWORD-mirror network </strong>(file name "<em>SWORD_mirror</em>"): The SWORD-mirror network was constructed to facilitate the SWORD-TopoCat network merging process (i.e., output of Step 3.1 in Figure "<em>SWORD-PLD_harmonization_steps.jpg</em>"). It is essentially <strong>a replica of SWORD except that the original SWORD reaches are geometrically modified to be aligned with the topological/hydrographic information depicted in MERIT Hydro</strong>. The SWORD-mirror network consists of four features:</p> <p> (a) SWORD-original reaches: SWORD_original_reaches_pfaf_xx<br> (b) SWORD-mirror prelim. reaches: SWORD_mirror_prelim_reaches_pfaf_xx<br> (c) SWORD-mirror reaches: SWORD_mirror_reaches_pfaf_xx<br> (d) SWORD-mirror reach catchments: SWORD_mirror_reach_catchments_pfaf_xx</p> <p><strong>5. Merged SWORD-mirror – TopoCat network </strong>(file name "<em>SWORD_TopoCat_merged</em>"): This dataset is the output of Step 3.2 in Figure "<em>SWORD-PLD_harmonization_steps.jpg</em>". It is essentially the merged product of the inter-lake reaches (from Step 2) and SWORD-mirror reaches (from Step 3.1). The merged SWORD-mirror – TopoCat network consists of three features:</p> <p> (a) Merged SWORD-TopoCat reaches: SWORD_TopoCat_merged_reaches_pfaf_xx<br> (b) SWORD nodes at SWORD-TopoCat confluence: SWORD_TopoCat_confluence_nodes_pfaf_xx<br> (c) Reach catchments for merged network: SWORD_TopoCat_reach_catchments_pfaf_xx</p> <p>The attribute tables for each of the feature components are explained in Section 4 of the product description document. All files of HarP are available in both shapefile and geodatabase formats.</p> <p> </p> <p><strong>Disclaimer</strong><br>Authors of this dataset claim no responsibility or liability for any consequences related to the use, citation, or dissemination of HarP. For any quesitons, please contact Safat Sikder and Jida Wang.</p>
Zooplankton functional trait database for Canadian lakes
<p>This dataset contains functional traits of 102 crustacean zooplankton taxa sampled in 624 Canadian lakes (Pelagic sample), as well as 58 sub-fossil cladoceran taxa (Sediments sample) sampled in 101 lakes. Lakes were sampled across Canada as part of the NSERC Canadian LakePulse Network. The traits used are: feeding type (B(<em>Bosmina</em>)-filtration, C(<em>Chydorus</em>)-filtration, D(<em>Daphia</em>)-filtration, S(<em>Sidae</em>)-filtration, stationary suspension or raptorial), habitat (littoral, pelagic or intermediate) and trophic group (carnivore, herbivore, omnivore, or a combination of these). Pelagic species length of up to 10 individuals per taxon per lake were measured by BSA Environmental Services (Ohio, U.S.A.), and averaged for each taxon. Sediments sample lengths were either obtained from the literature (Demott & Kerfoot, 1982; Barnett et al., 2007; Griffiths et al., 2019), or from the Pelagic sample length data. Feeding type, habitat and trophic group functional traits were obtained from literature (Demott & Kerfoot, 1982; Barnett et al., 2007; Hébert et al., 2016; Griffiths et al., 2019).</p> <p>References</p> <p>Barnett, A. J., Finlay, K., & Beisner, B. (2007). Functional diversity of crustacean zooplankton communities: Towards a trait-based classification. <em>Freshwater Biology</em>, <em>52</em>(5), 796–813. https://doi.org/10.1111/j.1365-2427.2007.01733.x</p> <p>Demott, W. R., & Kerfoot, W. C. (1982). Competition among cladocerans: nature of the interaction between Bosmina and Daphnia. <em>Ecology</em>, <em>63</em>(6), 1949–1966. https://doi.org/10.2307/1940132</p> <p>Griffiths, K., Winegardner, A. K., Beisner, B. E., & Gregory-Eaves, I. (2019). Cladoceran assemblage changes across the Eastern United States as recorded in the sediments from the 2007 National Lakes Assessment, USA. <em>Ecological Indicators</em>, <em>96</em>, 368–382. 061</p> <p>Hébert, M.-P., Beisner, B. E., & Maranger, R. (2016). A compilation of quantitative functional traits for marine and freshwater crustacean zooplankton. Ecology. https://doi.org/10.1890/15-1275</p>
LAGOS-NE-LOCUS v1.01: 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: 1925-2013
This data package, LAGOS-NE-LOCUS v1.01, 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-NEGEO 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-LOCUS v1.01 module includes information on the physical location and features of all lakes > 4 ha. The information provided for this population of lakes includes: lake unique identifiers, lake area, perimeter, latitude and longitude, and the zone IDs that the lake is located within (e.g., state, county, the hydrologic unit at each level (4, 8, and 12). Citation for
LAGOS-NE-GEO v1.05: 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: 1925-2013
This data package, LAGOS-NE-GEO v1.05, 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: lake location and physical characteristics for all lakes. (2) LAGOS-NE-GEO: 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: 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-NEGEO 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-GEO v1.05 module includes information on the ecological context of the census lakes, all lakes > 4 ha in the study extent, their watersheds, and their regions. The information provided in the data tables for this module is organized into three main themes: CHAG - climate, hydrology, atmospheric deposition of nitrogen and sulfur, and surficial geology; LULC - land use/cover, impervious co
Natural Lake Database in China in 2015 (NLD_China2015)
<p>The first database of natural lakes with an area > 0.01 km<sup>2</sup> in China in 2015 (NLD_China2015). The database was manually developed in reference to the existing lake inventories, reservoir datasets, and high-resolution images from Google Earth.</p> <p>The details of the NLD_China2015 is described in "<a href="https://zenodo.org/api/files/9e400087-179e-433e-8b59-3b9348557542/LakeDatabase_China2015_Readme_V1.0.docx">LakeDatabase_China2015_Readme_V1.0.docx</a>".</p>
Database of Himalayan glacial lakes
<p>This dataset contains a shapefile of 2231 Himalayan glacial lakes ranging in size between 875 m<sup>2</sup> to 5.6 km<sup>2</sup>. The lakes were manually digitized using high-resolution imagery in GoogleEarth in 2015. The dataset has been mapped and used by <a href="https://doi.org/10.1088/1748-9326/11/7/074005">Schwanghart et al. (2016)</a>. In addition, the dataset contains a shapefile of the great circle that describes the Himalayan Arc (<a href="http://10.1130/dx.doi.org/0091-7613(2001)029<0791:HPITHA>2.0.CO;2">Bendick and Bilham, 2001</a>) as well as a polygon shape which segments the Himalayan arc along the the great circle into 99 polygon.</p> <p><strong>References</strong></p> <p>Bendick, R. and Bilham, R.: How perfect is the Himalayan arc?, Geology, 29, 791–794, <a href="https://doi.org/10.1130/0091-7613(2001)029<0791:HPITHA>2.0.CO;2">https://doi.org/10.1130/0091-7613(2001)029<0791:HPITHA>2.0.CO;2</a>, 2001.</p> <p>Schwanghart, W., Worni, R., Huggel, C., Stoffel, M., and Korup, O.: Uncertainty in the Himalayan energy–water nexus: estimating regional exposure to glacial lake outburst floods, Environ. Res. Lett., 11, 074005, <a href="https://doi.org/10.1088/1748-9326/11/7/074005">https://doi.org/10.1088/1748-9326/11/7/074005</a>, 2016.</p>
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
Natural Lake Database in China in 2015 (NLD_China2015)
<p>The first database of natural lakes with an area > 0.01 km<sup>2</sup> in China in 2015 (NLD_China2015). The database was manually developed in reference to the existing lake inventories, reservoir datasets, and high-resolution images from Google Earth.</p>
Glacier Lake Outburst Flood Database
<p>This dataset is an inventory of globally occurred Glacier Lake Outburst Floods (GLOFs). Our database encompasses data from 769 different sources including satellite and aerial images, reports from local authorities, scientific publications, news outlets, workshop proceedings, social media posts, and unpublished work.</p> <p><strong>Files: </strong><br> <em>glofdatabase_V3.ods</em>: Database spreadsheet (OpenOffice file) containing all reported GLOFs.<br> <em>Parameter_Readme.ods:</em> Readme file describing all database parameters (i.e. columns in glofdatabase_V3.ods) and their units.</p> <p>Our database is an ongoing project and we offer a web-based, interactive map that grants access to the most recent state of the database (<a href="http://glofs.geoecology.uni-potsdam.de/">http://glofs.geoecology.uni-potsdam.de</a>). Users can also download all previous versions of the database from this interface.</p>
Data for cyanobacteria, nutrients and color from 588 lakes in Finland Norway Sweden and UK extracted from the WISER database
<p>Data on phosphorus, color, cyanobacteria biovolume, total phytoplankton biovolume and cyanobacteria proportion of the total phytoplankton biovolume used for GAMM</p>
FishPass Sortable Attribute Database: Phenological, morphological, physiological, and behavioural characteristics related to passage and movement of Great Lakes fishes
<p>In-stream barriers pose threats to fishes, including habitat loss, constraints on migration, and reduced connectivity between populations. Despite many negative consequences, barriers can serve to protect native species by limiting the spread of invasive species. For example, in the Laurentian Great Lakes, physical barriers have long been used to control invasive Sea Lamprey (<em>Petromyzon marinus</em>) populations by limiting access to potential upstream spawning and rearing habitat. Selective fish passage systems could solve this connectivity conundrum but must efficiently pass multiple native or desirable species while blocking invasive species. Designing such fish passage systems requires an understanding of the phenology, morphology, physiology, and behaviour (attribute dimensions) of fishes in the community. Here, we describe the first comprehensive collection of sortable attributes associated with fish passage. The integrated database consists of 21 biological attributes that influence the movement and passage of 220 species in the Great Lakes. Data coverage varies with species, taxonomic orders, and attribute dimensions. Behavioural attributes were typically underrepresented in the literature and the ecology of potential invaders was not well understood. The synthesis described herein is a critical step towards a holistic approach to fish passage design and may help to inform management actions related to population connectivity.</p>
Lake-TopoCat: A global Lake drainage Topology and Catchment database
<p><strong>Contact</strong>: Md Safat Sikder (mssikder@illinois.edu), Jida Wang (jidaw@illinois.edu)</p> <p> </p> <p><strong>Citation</strong></p> <p>If you use Lake-TopoCat, please cite the following paper:</p> <p>Sikder, M. S., Wang, J., Allen, G. H., Sheng, Y., Yamazaki, D., Song, C., Ding, M., Crétaux, J.-F., and Pavelsky, T. M., 2023. Lake-TopoCat: A global lake drainage topology and catchment dataset. <em>Earth System Science Data</em>, 15, 3483-3511, <a href="https://doi.org/10.5194/essd-15-3483-2023">https://doi.org/10.5194/essd-15-3483-2023</a>.</p> <p> </p> <p><strong>Data description and components</strong><br>This version of Lake-TopoCat was constructed using the SWOT Prior Lake Database (PLD) v106 (<em>Wang et al.</em>, 2023) lake mask and the 3-arc-second-resolution hydrography dataset MERIT Hydro v1.0.1 (<em>Yamazaki et al.</em>, 2019). The drainage type of each PLD lake, such as isolated, inflow-headwater, headwater, flow-through, terminal, and coastal, was determined with assistance of MERIT Hydro-Vector (<em>Lin et al.</em>, 2021), a high-resolution river network dataset with spatially-variable drainage densities.</p> <p><br>For convenience, the global landmass (excluding Antarctica) was partitioned to 68 Pfafstetter Level-2 basins or regions, and the Lake-TopoCat data products were also organized based on these 68 regions, with their region or basin IDs shown in the Fig. 'Pfaf2_basins.jpg', attached to this database.</p> <p><br>Lake-TopoCat consists of five feature components, each with multiple attributes depicting lake drainage relationships. The five features are:</p> <p><strong>1. Lake boundaries:</strong> polygons of 5,893,363 PLD lakes, larger than 1 ha.</p> <p> File name: <em>Lakes_pfaf_xx </em>where, 'pfaf_xx' indicates the Pfafstetter Level-2 basin ID (shown in Fig. 'Pfaf2_basins.jpg')</p> <p><strong>2. Lake outlets:</strong> points representing outlet or pour points of each individual lake. There are multiple outlets from a multifurcation lake. We identified 5,983,642 outlets for 5,893,363 lakes, where 83,819 lakes (~1.4% of the global lakes) show bi/multifurcation.</p> <p> File name: <em>Outlets_pfaf_xx</em></p> <p><strong>3. Unit catchment:</strong> boundary polygons of catchment defining the drainage areas between cascading (i.e., immediately upstream and downstream) lake outlets. The count of unit catchments equal to the count of lake outlets, and bifurcation or multifurcation lakes have multiple local catchments. In total, the delineated catchments in Lake-TopoCat cover about 85.1 million km2, which is about 63% of the Earth’s land mass excluding the Antarctic.</p> <p> File name: <em>Catchments_pfaf_xx</em></p> <p><strong>4. Inter-lake reaches:</strong> line features defining the drainage networks that connect the lake outlets to the inland sinks or the ocean. About 11 million connecting reaches were generated among ~6 million outlets. The total length of these inter-lake connecting reaches is ~19 million km, which is at least 8.75 times longer than the SWOT-visible river reaches as depicted in the SWOT River Database (SWORD) v16 (<em>Altenau et al.</em>, 2021).</p> <p> File name: <em>Reaches_pfaf_xx</em></p> <p><strong>5. Lake-network basins:</strong> boundary polygons of the entire drainage area containing each inter-lake network (i.e., a complete basin from the headwater to an inland sink or the ocean for all basins containing lakes). A total of 108,985 lake-network basins were identified. Among them, endorheic basins account for 2.75% by count and 19.5% by area of all lake-network basins. These endorheic basins cover ~17.5% of global surface excluding Antarctica.</p> <p> File name: <em>Basins_pfaf_xx</em></p> <p>The attribute tables for each of the feature components are explained in Section 4 of the product description document. For user convenience, we release the preliminary Lake-TopoCat lake outlets, unit catchments, and inter-lake reaches, with the affix '_prelim' in the file names (explained in the attached product description document). We also provide the polygon boundaries of the 68 Pfafstetter basins or regions in the file named 'Pfaf2_regions'. All files of Lake-TopoCat are available in both shapefile and geodatabase formats.</p> <p> </p> <p><strong>Disclaimer</strong><br>Authors of this dataset claim no responsibility or liability for any consequences related to the use, citation, or dissemination of Lake-TopoCat.</p>
A trait database for Phytoplankton of temperate lakes: numerical file
<p>Phytoplankton is a choice ecological indicator of lake ecological quality. Microalgae composing this biological compartment display a large diversity of morphological, physiological and ecological features, which are useful for understanding the interactions they have with other biotic and abiotic elements. Such kind of information together with classical Utermöhl phytoplankton analyses are useful for lake management and basic science. We present here a reference database of morphological (cell and colony sizes, biovolumes, mobility apparatus, colony formation), functional (functional groups of Reynolds, Padisak and Kruk, zooplankton edibility groups), physiological (trophic capacities) and ecological traits (Brettum index values) of more than 1200 taxa often observed in temperate lakes. This database, maintained since the 70’s until nowadays is now realized open access. A scientific paper associated to this database presents an overview of its content.</p>
FishPass Sortable Attribute Database: Phenological, morphological, physiological, and behavioural characteristics related to passage and movement of Great Lakes fishes
Open the record for dataset details and reuse information.
Hamilton-KBS lake chemistry database, Hickory Corners, MI 1998-2011
This dataset contains water chemistry measurements for lakes sampled near the Michigan State University Kellogg Biological Station in Hickory Corners, MI (n=139 lakes). Lake chemistry and chlorophyll samples were collected using an integrated tube sampler of the entire epilimnion (epilimnion depth was determined based on temperature profile) with sampling occuring from May-October with multiple sampling events per year. Samples were collected from 1998-2011, with no samples collected for several years in the mid-2000s. The data prior to 2010 were primarily collected by university researchers but beginning in 2010 sampling was undertaken by a graduate student funded by the Gull Lake Quality Organization (GLQO) to support monitoring of Gull Lake and its inflow streams. Lake samples were processed in the lab of Steve Hamilton, Michigan State University Kellogg BIological Station researcher.
USEPA EMAP Surface Waters Lake Database Northeast Lake Water Chemistry Data, 1991-1994
The primary function of the lake water chemistry samples, collected with a van Dorn sampler, is to determine acid-base status, trophic state, and classification of water chemistry type. Water chemistry in lakes is analyzed for two purposes. First, to understand the chemical habitat within which biota must exist so that we can understand the biological potential of the system and second, to evaluate the chemical quality of the water for the purposes of determine the potential stresses to which the biota are exposed. Water chemistry parameters are reported for one sample taken at the location of the deepest part of the lake by a van Dorn sampler from a depth of 1.5 m. These include: aluminum, alkalinity, acid neutralizing capacity, calcium, carbonate, color, specific conductance, dissolved inorganic carbon, dissolved organic carbon, bicarbonate, potassium, magnesium, ammonium, sodium, nitrate, total nitrogen, pH, total phosphorus, silica, total suspended solids, turbidity, and chlorophyll-a. Sampling was initiated July 1991 and ended September 1994.
Vermont Department of Environmental Conservation. Vermont Water Quality Data Archive and Lake Inventory Database from 1977 to 2010. Waterbury, VT
VT’s long-term archive of lake physical and chemical water quality. Maintained on a Sequel Server platform. Database integrates measurements from 1977 to present, and is continually being updated and augmented. Numerous parameters are archived within the database.
Global Lake and River Ice Phenology Database, Version 1
The Global Lake and River Ice Phenology Database contains freeze and thaw/breakup dates as well as other descriptive ice cover data for 865 lakes and rivers in the Northern Hemisphere. Of the 542 water bodies that have records longer than 19 years, 370 of them are in North America and 172 are in Eurasia. 249 lakes and rivers have records longer than 50 years, and 66 have records longer than 100 years. A few water bodies have data available prior to 1845. This database, with water bodies distributed around the Northern Hemisphere, allows for the analysis of broad spatial patterns as well as long-term temporal patterns.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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