A Global Lakes/Reservoirs Surface Extent Dataset (GLRSED): An Integration of Multi‐Source Data
ABSTRACT The surface water extent of global lakes/reservoirs is a fundamental input data for many studies. Although some datasets are currently available, issues such as incomplete data or spatial inconsistencies persist. In this study, a new Global Lakes/Reservoirs Surface Extent Dataset (GLRSED),...
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Wiley
2025-01-01
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| Series: | Geoscience Data Journal |
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| Online Access: | https://doi.org/10.1002/gdj3.285 |
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| author | Bingxin Bai Lixia Mu Yumin Tan |
| author_facet | Bingxin Bai Lixia Mu Yumin Tan |
| author_sort | Bingxin Bai |
| collection | DOAJ |
| description | ABSTRACT The surface water extent of global lakes/reservoirs is a fundamental input data for many studies. Although some datasets are currently available, issues such as incomplete data or spatial inconsistencies persist. In this study, a new Global Lakes/Reservoirs Surface Extent Dataset (GLRSED), which provides a more comprehensive spatial extent and basic attributes (e.g., name, area, source, depth and type) of 2.17 million individual features, was developed based on HydroLAKES and OpenStreetMap (OSM). In addition, by spatially overlaying with mountainous polygon, lakes/reservoirs in mountainous areas were identified. The Global Reservoir and Dam database (GRanD), GlObal geOreferenced Database of Dams (GOODD), Georeferenced global Dams and Reserves (GeoDAR) dataset, and OSM were used to distinguish reservoirs from natural lakes. The lakes/reservoirs in the rivers were identified by overlaying them with the Surface Water and Ocean Topography (SWOT) Mission River Database (SWORD). Similarly, endorheic, glacier‐fed and permafrost‐fed lakes/reservoirs were identified using the same method. Furthermore, the coverage of the SWOT ground track for each lake/reservoir in the GLRSED was calculated to explore the potential of SWOT in monitoring water resources. Although preliminary and with some limitations, this dataset is promising. It can provide essential data for monitoring global lakes/reservoirs, support refined water resource management, and facilitate comprehensive studies on the impacts of human activities and climate change on these water bodies. |
| format | Article |
| id | doaj-art-936b2f25a1a146d58661732f55c6fd95 |
| institution | Kabale University |
| issn | 2049-6060 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
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| series | Geoscience Data Journal |
| spelling | doaj-art-936b2f25a1a146d58661732f55c6fd952025-01-27T08:26:33ZengWileyGeoscience Data Journal2049-60602025-01-01121n/an/a10.1002/gdj3.285A Global Lakes/Reservoirs Surface Extent Dataset (GLRSED): An Integration of Multi‐Source DataBingxin Bai0Lixia Mu1Yumin Tan2Department of Marine Technology Ocean University of China Qingdao ChinaDepartment of Marine Technology Ocean University of China Qingdao ChinaSchool of Transportation Science and Engineering Beihang University Beijing ChinaABSTRACT The surface water extent of global lakes/reservoirs is a fundamental input data for many studies. Although some datasets are currently available, issues such as incomplete data or spatial inconsistencies persist. In this study, a new Global Lakes/Reservoirs Surface Extent Dataset (GLRSED), which provides a more comprehensive spatial extent and basic attributes (e.g., name, area, source, depth and type) of 2.17 million individual features, was developed based on HydroLAKES and OpenStreetMap (OSM). In addition, by spatially overlaying with mountainous polygon, lakes/reservoirs in mountainous areas were identified. The Global Reservoir and Dam database (GRanD), GlObal geOreferenced Database of Dams (GOODD), Georeferenced global Dams and Reserves (GeoDAR) dataset, and OSM were used to distinguish reservoirs from natural lakes. The lakes/reservoirs in the rivers were identified by overlaying them with the Surface Water and Ocean Topography (SWOT) Mission River Database (SWORD). Similarly, endorheic, glacier‐fed and permafrost‐fed lakes/reservoirs were identified using the same method. Furthermore, the coverage of the SWOT ground track for each lake/reservoir in the GLRSED was calculated to explore the potential of SWOT in monitoring water resources. Although preliminary and with some limitations, this dataset is promising. It can provide essential data for monitoring global lakes/reservoirs, support refined water resource management, and facilitate comprehensive studies on the impacts of human activities and climate change on these water bodies.https://doi.org/10.1002/gdj3.285globalHydroLAKESlakes/reservoirssurface extent |
| spellingShingle | Bingxin Bai Lixia Mu Yumin Tan A Global Lakes/Reservoirs Surface Extent Dataset (GLRSED): An Integration of Multi‐Source Data Geoscience Data Journal global HydroLAKES lakes/reservoirs surface extent |
| title | A Global Lakes/Reservoirs Surface Extent Dataset (GLRSED): An Integration of Multi‐Source Data |
| title_full | A Global Lakes/Reservoirs Surface Extent Dataset (GLRSED): An Integration of Multi‐Source Data |
| title_fullStr | A Global Lakes/Reservoirs Surface Extent Dataset (GLRSED): An Integration of Multi‐Source Data |
| title_full_unstemmed | A Global Lakes/Reservoirs Surface Extent Dataset (GLRSED): An Integration of Multi‐Source Data |
| title_short | A Global Lakes/Reservoirs Surface Extent Dataset (GLRSED): An Integration of Multi‐Source Data |
| title_sort | global lakes reservoirs surface extent dataset glrsed an integration of multi source data |
| topic | global HydroLAKES lakes/reservoirs surface extent |
| url | https://doi.org/10.1002/gdj3.285 |
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