To construct hydrological models, hypotheses are formulated based on hydrological knowledge. The essence of hydrological model development is the trade-off between model parsimony and adequacy in terms of process representation. The relationship between large quantitative and qualitative data sets across spatial and temporal scales with increasing availability and the way processes are implemented in models is an ongoing discussion.
In this session we welcome contributions on the interaction between data and models with the aim of improving process understanding and representation in their spatio-temporal dynamics.
Potential contributions may include (but not limited to):
(1) Improving model structural adequacy informed by cutting-edge hydrological data and knowledge;
(2) Better representing often neglected processes in hydrological models such as human impacts, river regulations, irrigation, as well as vegetation dynamics;
(3) Improving the characterization of spatio-temporal dynamics of internal and external model fluxes;
(4) Upscaling experimentalists' knowledge from smaller to larger scale by identifying driving forces for spatial patterns;
(5) Better monitoring and seamless modeling of spatial patterns in hydrology and land surface models using distributed earth observations;
(6) The development of novel approaches and performance metrics for evaluating and constraining models in space and time.
(7) How can hydrological models be adapted to be able to extrapolate to changing conditions, including changing vegetation dynamics? (From the initiative of 23 Unsolved Problems in Hydrology, https://doi.org/10.1080/02626667.2019.1620507)
This session is organized as part of the grass-root modelling initiative on "Improving the Theoretical Underpinnings of Hydrologic Models" launched in 2016.

Invited Speakers:

Susan Steele-Dunne from Delft University of Technology on "Advances in using radar to observe vegetation water dynamics"
and
Hylke Beck from Princeton University on "Towards global fully-distributed regionalization of hydrological model parameters."