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47 results for “Lakes and reservoirs”
FIGURE 3 in Biogeography and co-occurrence of 16 planktonic species of Keratella Bory de St. Vincent, 1822 (Rotifera, Ploima, Brachionidae) in lakes and reservoirs of the United States
FIGURE 3. Box and whisker plot showing elevation range (m) by quartile for 15 species of Keratella.
Data for 'Plastic debris in lakes and reservoirs'
<p>Dataset and R code for the manuscript entitled 'Plastic debris in lakes and reservoirs' by Nava et al. (<a href="http://www.nature.com/articles/s4186-023-06168-4">www.nature.com/articles/s4186-023-06168-4</a>) - Article DOI: 10.1038/s41586-023-06168-4</p>
Pre SWOT Hydrology Global Lake/Reservoir Storage Time Series V2
The Global Lake/Reservoir Storage Time Series is derived from the Surface Water Height Time Series and Surface Water Extent Mask Time Series products. The purpose of this dataset is to provide surface water storage estimates for several hundred lakes and reservoirs across the globe. These time series potentially span a 25 year time period, from late 1992 to 2017, satisfying the project goal of ESDR creation with a suitable level of quality that supports long-term trend analysis and global water dynamics models. This product is readily accessible and is of direct use to both water managers and the scientific community worldwide, and allows for improved assessment and modeling of the human impact on the global water cycle. These pre SWOT data are derived from satellites to provide hydrological measurements. The Surface Water and Ocean Topography (SWOT) mission will have hydrology as one of its objectives. This dataset does not have the same variables as SWOT, but does provide hydrological measurements with typical quality flagging typical of satellite data. Not only does it provide science information, it can also assist hydrological users new to satellite data with the satellite data formats and variables before SWOT launches.
Pre SWOT Hydrology Global Lake/Reservoir Surface Inland Water Height GREALM V.2
The Global Lake/Reservoir Surface Inland Water Height Time Series is derived from the G-REALM10 lake level product https://ipad.fas.usda.gov/cropexplorer/global_reservoir/ The purpose of this dataset is to provide surface water dynamics for several hundred lakes and reservoirs across the globe. These time series potentially span a 25 year time period, from late 1992 to 2017, satisfying the project goal of ESDR creation with a suitable level of quality that supports long-term trend analysis and global water dynamics models. Water level variation is also a key component required for the determination of surface water storages and fluxes. This product is readily accessible and is of direct use to both water managers and the scientific community worldwide, and allows for improved assessment and modeling of the human impact on the global water cycle. These pre SWOT data are derived from satellites to provide hydrological measurements. The Surface Water and Ocean Topography (SWOT) mission will have hydrology as one of its objectives. This dataset does not have the same variables as SWOT, but does provide hydrological measurements with typical quality flagging typical of satellite data. Not only does it provide science information, it can also assist hydrological users new to satellite data with the satellite data formats and variables before SWOT launches.
Pre SWOT Hydrology Global Lake/Reservoir Surface Inland Water Area Extent V2
The Global Lake/Reservoir Surface Inland Water Extent Mask Time Series are derived from the MODIS instruments. The purpose of this dataset is to provide surface water dynamics for several hundred lakes and reservoirs throughout the globe, with a base temporal resolution of 8 days and a spatial resolution of 500 meters. With the exception of periods of low-quality input data, these time series will extend across the lifespan of the MODIS multispectral reflectance products, from roughly 2000 to present. These time series will allow us to satisfy the project goal to produce ESDRs of suitable quality to support long-term trend analysis and global water dynamics models for the longest length possible (in most cases, about 20 years, the length of the altimetry record) of key measures of surface water storages and fluxes. This product should be accessible and of direct use to both water managers and the scientific community worldwide, and will allow for improved assessment and modeling of human impact on the global water cycle. These pre SWOT data are derived from satellites to provide hydrological measurements. The Surface Water and Ocean Topography (SWOT) mission will have hydrology as one of its objectives. This dataset does not have the same variables as SWOT, but does provide hydrological measurements with typical quality flagging typical of satellite data. Not only does it provide science information, it can also assist hydrological users new to satellite data with the satellite data formats and variables before SWOT launches.
3D-LAKES: A Three-Dimensional Global Lake and Reservoir Bathymetry Utilizing ICESat-2 Altimetry and Landsat Imagery
<p>This study introduces the 3D-Global Lakes (3D-LAKES) dataset, which includes the area-elevation (A-E) relationship and three-dimensional bathymetry for 510,530 global lakes and reservoirs, representing 98.9% of global surface water storage capacity. In this Zenodo, Level 1 (L1) and Level 2 (L2) A-E relationships are provided. L1 products were created using ICESat-2 and Landsat satellites, while L2 products, apply interpolation and extrapolation to L1 products, may contain errors. For detailed structure and format information, please read the "README" file included in the repository.</p> <p>Furthermore,</p> <p>You can view the A–E relationships and 3D bathymetry maps interactively through the Google Earth Engine (GEE) application. Please visit <a href="https://planet-test-projectchi.projects.earthengine.app/view/d-lakes" target="_new" rel="noreferrer">this link</a>.</p> <p>For downloading the 3D Bathymetry maps, please visit either the <strong><a href="https://code.earthengine.google.com/071edead921f56ae44f67888528f854c" target="_blank" rel="noopener">Google Earth Engine (GEE) code</a></strong> or the <strong><a href="https://colab.research.google.com/drive/15yRD3E06zmsm4tAF-mBz-DhHvIKNq1Lh?usp=drive_link" target="_blank" rel="noopener">Python version</a></strong> of the code.</p> <p>For detailed methodology and validation, see Huang (2025)*.</p> <p>Huang, C.H., Zhang, S., Shah, D. <em>et al.</em> 3D-LAKES: Three-Dimensional Global Lake and Reservoir Bathymetry from ICESat-2 Altimetry and Landsat Imagery. <em>Sci Data</em> <strong>12</strong>, 1625 (2025). https://doi.org/10.1038/s41597-025-05911-y</p> <p> </p>
Deoxygenation Exacerbates Nitrous Oxide Emissions Evidenced from Global Lakes and Reservoirs
<p>This is a dataset for describing global N2O from lakes and reservoirs.</p>
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