Large-sample hydrology datasets have advanced hydrological research, yet the impact of landscape map details on identifying dominant streamflow generation processes remains underexplored. This study investigates the role of geology using maps of increasing detail – global, continental, and regional – each reclassified into four permeability classes. These geological attributes were used along with topography, soil, land use, and climate attributes to identify dominant controls on streamflow signatures across 4469 European catchments. To distinguish landscape influences from the otherwise dominant influence of climate, we conducted separate analyses on nested basins. Three scales were considered to assess scale-dependent patterns: large (63 nested basins), intermediate (the Moselle nested basin), and small (five nested catchments within the Moselle). The large-scale study used geology information from global and continental maps, while the others also incorporated regional maps. At the large scale, dominant controls varied widely between nested basins, but landscape generally outweighed climate, highlighting the value of our nested basin design. At this scale, continental and global geology maps produced different correlation patterns, with neither consistently superior. At the intermediate scale, increased geological detail led geology to shift from the least to the most correlated variable for certain streamflow signatures. The small-scale experiment reinforced these findings, as the regional map highlighted controls more consistent with process understanding. This study underscores the benefit of integrating detailed, region-specific geological data into large sample hydrology studies, and demonstrates the utility of a nested basins design. These findings have important implications for hydrological regionalization and streamflow prediction in ungauged basins.

Large-sample hydrology datasets have become increasingly available, contributing to significant scientific advances. However, in Europe, only a few such datasets have been published, capturing only a fraction of the wealth of information from national data providers in terms of available spatial density and temporal extent. We present “EStreams”, an extensive dataset of hydro-climatic variables and landscape descriptors and a catalogue of openly available stream records for 17,130 European catchments. Spanning up to 120 years, the dataset includes streamflow indices, catchment-aggregated hydro-climatic signatures and landscape attributes (topography, soils, geology, vegetation and landcover). The catalogue provides detailed descriptions that allow users to directly access streamflow data sources, overcoming challenges related to data redistribution policies, language barriers and varied data portal structures. EStreams also provides Python scripts for data retrieval, aggregation and processing, making it dynamic in contrast to static datasets. This approach enables users to update their data as new records become available. Our goal is to extend current large-sample datasets and further integrate hydro-climatic and landscape data across Europe.