URA dataset - 40 Basque Country catchments hourly hydro-meteorological data

Basque Country is located in north of Spain on the Atlantic coast. This region, characterized by its humid climatology, has abundant water resources. The catchments, noted for their flashy and humid characteristics, span an area of 4494 Km2 and include a diverse range of basin sizes from 4 to 1000 Km2. The Basque Water Agency (URA), a regional governmental entity in the Basque Country, is responsible for managing water policies and resources in this territory. To support water resources planning and management, URA has compiled a high-quality dataset suitable for data mining using deep learning models. This dataset includes hourly hydro-meteorological timeseries, reflecting the region’s steep, flashy, and humid hydrological dynamics. URA catchments are situated between the Cantabrian Mountains (reaching up to 1300 meters in elevation) in the northwest and the Atlantic Ocean to the north. The region is predominantly covered by grasslands and evergreen forests and benefits from the warming effects of the Gulf Stream. The climate is humid and temperate, with mean annual temperatures ranging from 9°C in the mountains to 15°C in lower regions. Annual rainfall varies between 1200 and 1600 millimeters, primarily due to the advection of North Atlantic fronts. URA has collected hourly hydro-meteorological timeseries from approximately 100 stations distributed across the region, including rain gauges and water level measurement sites. Accurate rainfall-runoff modeling is critical in this region due to its susceptibility to flash floods. This dataset presents 21 years of hourly timeseries from 40 catchments within the region. This extensive temporal coverage and high-resolution data offer valuable insights into the region’s hydrological dynamics. This Dataset is published with the papers: 1- "Ensemble Learning of Catchment-Wise Optimized LSTMs Enhances Regional Rainfall-Runoff modelling - Case Study: Basque Country, Spain" Hosseini et al., 2024. (Preprint - Under review J.Hydro 2024) Available at SSRN: https://ssrn.com/abstract=4918782 2- "Hyperparameter Optimization of Regional Hydrological LSTMs by Random Search: A Case Study from Basque Country, Spain" (Accepted on 29th Aug 2024); "Hosseini et al., (2024), Precise Tuning of Regional Hydrological Lstm Networks: Simultaneous Systematic Random Search Optimization. Available at SSRN: https://ssrn.com/abstract=4815562 or http://dx.doi.org/10.2139/ssrn.4815562" (Preprint)