Over the past decades, hydrology as a discipline has evolved in many ways. It is currently viewed as a key geoscience for understanding short and long term impact of global change. Within this broad discipline, hydrologists address a variety of water-related issues, from soil processes and vegetation [1, 2], to surface- and groundwater [3, 4], to biogeochemical transformation [5]. In addition to the local scale processes, large-scale hydrology implies strong interactions between catchment dynamics and the climate system affecting both water quantity and quality [6, 7]. Resolving hydrological processes rigorously based on physics still poses serious challenges in spite of the signifcant progress. The main reason is that natural systems exhibit variability in space and time on multiple scales, requiring novel approaches that combine physics with probabilistic scaling concepts [8]. It is only through physics-based bottom-up approaches combined with insightful synthesis of top-down approaches that hypotheses, theory and observations can converge.

With the increasing capabilities of computational sciences, powerful tools have emerged, advancing the field. While High Performance Computing opens interesting perspectives for advancing our understanding of transport processes across scales, from pore to catchment scale and beyond, physics-based descriptions are critical for identifying dominant couplings and suitable scale-dependent parametrizations. Furthermore, recent scientifc discoveries show complex properties of water on the molecular scale [9]. This calls for deeper understanding of water properties based on molecular interactions across the whole water phase diagram, affected by interfaces and confned geometries such as pores [10].

The purpose of this conference is to help bridge knowledge gaps in hydrology by promoting dynamic approaches and process rigour in topics ranging from the molecular scale interactions to the heterogeneous subsurface and dynamic catchments. These are implemented in novel ways in order to enhance our process understanding and improve methods for engineering applications.