Introducing the BULL Database – Spanish Basin attributes for Unraveling Learning in Large-sample hydrology
- 1Department of Civil Engineering, Universidad Católica San Antonio de Murcia, Campus de Los Jerónimos s/n, Guadalupe, Murcia 30107, Spain
- 2Department of Civil Engineering, Universidad de Las Palmas de Gran Canaria, Campus de Tafira, Las Palmas de Gran Canaria 35017, Spain
Large-Sample Hydrology (LSH) plays a crucial role in understanding different hydrological processes, using large basin datasets as fundamental resources that allow researchers to explore multiple facets of hydrology (Addor et al. 2020). In recent years, multiple LSH datasets adapted to the national scale have been developed. We present BULL, a novel basin dataset for large-sample hydrological studies in Spain. BULL includes data from 503 watersheds, providing daily hydrometeorological time series (streamflow and climatic variables) and attributes related to basin characteristics. To collect these attributes, the recommendations included in the CARAVAN (Kratzert et al. 2023) initiative for the generation of a truly open global hydrological dataset have been followed. BULL covers the entire territory of Peninsular Spain, which is characterized by its wide climatic and hydrological variability, including catchments ranging from 100 km2 to 2000 km2. One of the main novelties of BULL to other national-scale datasets is the analysis of the hydrological alteration of the basins included in this dataset. The hydrological alteration is calculated by statistical comparison of the monthly flow values measured in the gauges and the flow values obtained from the Integrated System for Rainfall-Runoff Model (SIMPA) (Estrela and Quintas, 1996) developed by the Center for Hydrographic Studies (CEDEX), for the entire Spanish territory. This aspect is especially important in countries such as Spain, which is characterized as one of the countries in the world where rivers suffer from the highest levels of anthropization. The BULL dataset is made freely available to scientific users via the open-access repository Zenodo.
References:
Addor, N., Do, H.X., Alvarez-Garreton, C. et al. Large-sample hydrology: recent progress, guidelines for new datasets and grand challenges. Hydrological Sciences Journal 65, 712–725 (2020). https://doi.org/10.1080/02626667.2019.1683182
Estrela, T., Quintas, L., 1996. A distributed hydrological model for water resources assessment in large basins. Proceedings of 1st International Conference on Rivertech. Vol. 96, pp. 861–868.
Kratzert, F., Nearing, G., Addor, N. et al. Caravan - A global community dataset for large-sample hydrology. Sci Data 10, 61 (2023). https://doi.org/10.1038/s41597-023-01975-w
How to cite: Senent-Aparicio, J., Castellanos-Osorio, G., Segura-Méndez, F., López-Ballesteros, A., Jimeno-Sáez, P., and Pérez-Sánchez, J.: Introducing the BULL Database – Spanish Basin attributes for Unraveling Learning in Large-sample hydrology, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8081, https://doi.org/10.5194/egusphere-egu24-8081, 2024.
