GeoDAR: georeferenced global dams and reservoirs dataset for bridging attributes and geolocations

Abstract. Dams and reservoirs are among the most widespread human-made infrastructures on Earth. Despite their societal environmental significance, spatial inventories of dams reservoirs, even for large ones, insufficient. A dilemma existing georeferenced dam datasets is polarized focus either quantity coverage (e.g., GlObal geOreferenced Database Dams, GOODD) or detailed attributes a limited region GRanD (Global Reservoir Dam database) national inventories). One comprehensive datasets, World Register (WRD), maintained by International Commission Large (ICOLD), documents nearly 60 000 with an extensive suite attributes. Unfortunately, WRD records provide no geographic coordinates, limiting benefits spatially explicit applications. To bridge gap between attribute accessibility explicitness, we introduce Georeferenced global And Reservoirs (GeoDAR) dataset, created utilizing Google Maps geocoding application programming interface (API) multi-source inventories. We release GeoDAR in two successive versions (v1.0 v1.1) at https://doi.org/10.5281/zenodo.6163413 (Wang et al., 2022). v1.0 holds 22 560 points from WRD, whereas v1.1 consists (a) 24 783 after harmonization v1.3 (b) 21 515 reservoir polygons retrieved high-resolution water masks based one-to-one relationship reservoirs. Due to challenges, resolved ∼ 40 % which, however, comprise over 90 total area, catchment storage capacity. does not proprietary attributes, but upon individual user requests may assistance associating features information that users have acquired ICOLD. this limit, GeoDAR, triple GRanD, significantly enhances details smaller more complements other Along its extended accessibility, expected benefit broad range applications hydrologic modeling, resource management, ecosystem health, energy planning.