{rfName}
BU

Indexed in

License and use

Icono OpenAccess

Citations

5

Altmetrics

Grant support

This research was supported by the project TwinTagus from the Spanish Ministry of Science and Innovation under grant PID2021-128126OA-I00. Gerardo Castellanos-Osorio was supported by the Ministry of Science, Innovation and Universities of Spain under an FPI grant (PRE2022-101437).

Analysis of institutional authors

Lopez-Ballesteros, AdrianAuthor

Share

August 11, 2025
Publications
>
Article
Sí

BULL Database - Spanish Basin attributes for Unravelling Learning in Large-sample hydrology

Publicated to:Scientific Data. 11 (1): 737- - 2024-07-06 11(1), DOI: 10.1038/s41597-024-03594-5

Authors: Senent-Aparicio, Javier; Castellanos-Osorio, Gerardo; Segura-Mendez, Francisco; Lopez-Ballesteros, Adrian; Jimeno-Saez, Patricia; Perez-Sanchez, Julio

Affiliations

Catholic Univ San Antonio, Dept Civil Engn, Campus Jeronimos S-N, Murcia 30107, Spain - Author
Univ Las Palmas Gran Canaria, Dept Civil Engn, Campus Tafira, Las Palmas Gran Canaria 35017, Spain - Author

Abstract

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.

Keywords

Catchment attributesData setDatasetEnvironmental sciencesHydrometeorological time-seriesLandscape attributesMeteorologyPerformanceResourceRiver

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Scientific Data due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2024 there are still no calculated indicators, but in 2023, it was in position 15/135, thus managing to position itself as a Q1 (Primer Cuartil), in the category Multidisciplinary Sciences.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2025-08-22:

  • WoS: 2
  • Europe PMC: 1

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-08-22:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 7 (PlumX).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.