Climate and landscape jointly control European streamflow behaviour

Journal Article (2026)
Author(s)

Julia M. Rudlang (TU Delft - Civil Engineering & Geosciences)

Thiago V.M. do Nascimento (Eawag - Swiss Federal Institute of Aquatic Science and Technology, Universitat Zurich)

Ruud van der Ent (TU Delft - Civil Engineering & Geosciences)

Fabrizio Fenicia (Eawag - Swiss Federal Institute of Aquatic Science and Technology)

Markus Hrachowitz (TU Delft - Civil Engineering & Geosciences)

Research Group
Water Systems Monitoring & Modelling
DOI related publication
https://doi.org/10.5194/hess-30-4481-2026 Final published version
More Info
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Publication Year
2026
Language
English
Research Group
Water Systems Monitoring & Modelling
Journal title
Hydrology and Earth System Sciences
Issue number
14
Volume number
30
Pages (from-to)
4481-4508
Downloads counter
38
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Abstract

The complex composition of hydrological systems, climates and landscapes makes it challenging to explain and predict hydrological streamflow response. Many previous large-sample studies, mostly focused on the United States, identified climate as the primary control, with landscape exerting only a minor role in shaping hydrological behaviour. Yet, a few other studies report contradictory results with landscape being a more dominant driver. In this study, we use an unprecedented sample of more than 7000 catchments in Europe from the EStreams dataset to identify and map functionally similar catchments, together with their spatially variable climate and landscape controls. The wide spatial and temporal gradient of the study catchments was used to identify hydrological response types (HRTs) based on 40 hydrological streamflow signatures related to long-term averages and inter-annual variability of magnitude, timing, duration, frequency, and seasonality. Overall, 10 HRTs could be identified. Several HRTs are well defined and well distinguishable, largely due to catchments with strongly seasonal or more extreme behaviour. Other HRTs remain difficult to distinguish, as these catchments represent more transitional conditions with increasingly overlapping characteristics between HRTs. The underlying drivers of the HRTs were identified by using 84 climate- and landscape attributes to predict catchment membership to their respective HRT with a Random Forest classification model. Climate emerges as the dominant driver of hydrological behaviour at the continental scale. However, landscape was found, in 4 out of 10 HRTs, to be at least as strong or even stronger a control on the hydrological streamflow response. These results highlight that the complex, integrated nature of hydrological response remains challenging to disentangle, even with extensive datasets and advanced modelling approaches, and therefore, climate and landscape need to be understood as joint drivers in a co-evolutionary perspective.