Spatio-temporal dynamics of states and fluxes across the terrestrial compartments of the hydrological cycle lead to complex, scale-dependent patterns. Distributed physically-based hydrological models have the potential to shed light on the physical processes inherent to the occurrence of such patterns and to provide reliable spatio-temporal predictions. Realizing this potential require a paradigm shift that includes cross-disciplinary physical processes and that moves away from the aggregated evaluation of hydrological models towards a spatially distributed and multi-compartment approach. Recent advances in computational power and spatial data availability have prepared the ground for bringing the science forward. This session focuses on advances in distributed hydrological modelling with special attention to the progress made within spatial model evaluation/calibration (e.g., methodologies for incorporating spatial pattern information) and progress made in the representation of coupled hydrological processes (e.g., interactions and feedback with climate and vegetation as well as between water, energy and carbon cycles). Specifically, the ability of models to reproduce observed spatial patterns will be targeted. We encourage contributions in several areas:
• Development and testing of performance metrics specifically suited for evaluating spatial model performance
• Identification and quantification of driving forces that generate spatial patterns of hydrological states and fluxes.
• Model parameter regionalization and regularization approaches
• Calibration frameworks focusing on spatial model performance
• Case studies including spatial model evaluation e.g. examining or assessing rainfall, soil moisture, evapotranspiration, droughts or floods