Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/132733
Título: | BULL Database - Spanish Basin attributes for Unravelling Learning in Large-sample hydrology | Autores/as: | Senent-Aparicio, Javier Castellanos-Osorio, Gerardo Segura-Mendez, Francisco Lopez-Ballesteros, Adrian Jimeno-Saez, Patricia Pérez Sánchez, Julio |
Clasificación UNESCO: | 3301 Ingeniería y tecnología aeronáuticas 3308 Ingeniería y tecnología del medio ambiente |
Palabras clave: | Hydrometeorological Time-Series Landscape Attributes Catchment Attributes Environmental Sciences Data Set, et al. |
Fecha de publicación: | 2024 | Publicación seriada: | Scientific data | Resumen: | We present a novel basin dataset for large-sample hydrological studies in Spain. BULL comprises data for 484 basins, combining hydrometeorological time series with several attributes related to geology, soil, topography, land cover, anthropogenic influence and hydroclimatology. Thus, we followed recommendations in the CARAVAN initiative for generating a truly open global hydrological dataset to collect these attributes. Several climatological data sources were used, and their data were validated by hydrological modelling. One of the main novelties of BULL compared to other national-scale datasets is the analysis of the hydrological alteration of the basins included in this dataset. This aspect is critical in countries such as Spain, which are characterised by rivers suffering from the highest levels of anthropisation. The BULL dataset is freely available at https://zenodo.org/records/10605646. | URI: | http://hdl.handle.net/10553/132733 | ISSN: | 2052-4463 | DOI: | 10.1038/s41597-024-03594-5 | Fuente: | Scientific Data [ISSN 2052-4463], v. 11 (737), (Julio 2024) |
Colección: | Artículos |
Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.