Published June 7, 2023 | Version 1.0
Dataset Open

A Global Lake/Reservoir Surface Extent Dataset (GLRSED)

Description

Global lake/reservoir surface water extent is the basic input data for many studies. Although there are some datasets at present, there are problems such as incomplete or spatial inconsistency exist among them due to various reasons like different data sources and dynamic change characteristics of the surface water. Here, a new Global Lake/Reservoir Surface Extent Dataset (GLRSED) that contains spatial extent and basic attributes (e.g., name, area, lake type and source) of 2.17 million lakes/reservoirs was produced based on HydroLAKES, GRanD and OpenStreetMap. By spatially overlaying GLRSED with other auxiliary data, we identified mountain lakes, endorheic lakes, reservoirs, glacier-fed lakes and permafrost-fed lakes, etc. In addition, we calculated the Surface Water and Ocean Topography (SWOT) orbits passing through each lake. The dataset could provide basic data for global lake/reservoir monitoring, as well as the study on the impact of human actions and climate changes on lake/reservoir freshwater availability, etc.

Notes

This version is for peer-review.

Files

GLRSED_GeoPackage_V1.0.zip

Files (5.3 GB)

Name Size Download all
md5:8e11a6d6a88be409bd1bdc3fa321ec23
1.8 GB Preview Download
md5:6df66eb4ab64ca203d05c0d322dcf1ae
1.7 GB Preview Download
md5:dde01bdc310e2f624b4ae95b3e30d63a
1.7 GB Preview Download

Additional details

References

  • Bai et al. (2023). A Global Lake/Reservoir Surface Extent Dataset (GLRSED): An integration of HydroLAKES, GRanD and OpenStreetMap. (under review))
  • Altenau et al. (2021). The Surface Water and Ocean Topography (SWOT) Mission River Database (SWORD): A Global River Network for Satellite Data Products. Water Resources Research, 57(7), 1–15. https://doi.org/10.1029/2021WR030054
  • Messager et al. (2016). Estimating the volume and age of water stored in global lakes using a geo-statistical approach. Nature Communications, 7: 13603. https://doi.org/10.1038/ncomms13603
  • OpenStreetMap Contributors. (2022). Available online: https://www.openstreetmap.org (accessed on 12 December 2022)
  • Lehner et al. (2011). High-resolution mapping of the world's reservoirs and dams for sustainable river-flow management. Frontiers in Ecology and the Environment, 9(9), 494–502. https://doi.org/10.1890/100125
  • Korner et al. (2017). A global inventory of mountains for bio-geographical applications. Alpine Botany, 1–15. https://doi.org/10.1007/s00035-016-0182-6
  • Lehner et al. (2013). Global river hydrography and network routing: baseline data and new approaches to study the world's large river systems. HYDROLOGICAL PROCESSES, 2186(April), 2171–2186. https://doi.org/10.1002/hyp.9740
  • Mulligan et al. (2020). GOODD, a global dataset of more than 38, 000 georeferenced dams. Scientific Data, 1–8. https://doi.org/10.1038/s41597-020-0362-5
  • Wang et al. (2022). GeoDAR : georeferenced global dams and reservoirs dataset for bridging attributes and geolocations. Earth System Science Data, 14(April), 1869–1899. https://doi.org/10.5194/essd-14-1869-2022
  • Rignot et al. (2014). Ice-Shelf Melting Around Antarctica. Science, 266(2013), 266–270. https://doi.org/10.1126/science.1235798
  • ...