In hydrological modelling, assumptions regarding relevant hydrological processes in a catchment determine both the chosen model structures and model parameterisation.
Approaches used in hydrological modelling are in general only applicable at certain scales and boundary conditions. Unfortunately such approaches are often applied beyond these scales and boundary conditions without proper testing. Examples are the use of the Richard's equation at grid cells of 10s to 100s of meters, the use of Darcy in non-homogeneous aquifers and the use of the degree day approach in situations with significant advective energy transport. Model calibration (unintentionally) compensates for the deficiencies in model structure. This causes the risk of models being “right for the wrong reason” in calibration and thus being inapplicable for predictions.
The undaunted belief in and adherence to older, established concepts against scientific evidence is what has been termed hydromythology by Pomeroy et al. (2013).
During the past decades, new monitoring techniques have become available which provide a plethora of data to scrutinize well-established modelling concepts and to improve our hydrological process understanding (e.g. high-frequency monitoring of isotopes, water quality, and turbulent fluxes, remote sensing, citizen science), thus help us to overcome some hydromythologies.
In this session, we particularly welcome contributions that address one of the following topics:
(I) Studies challenging well-accepted theories with data
(II) Modelling studies including a critical assessment of calibration vs. evidence
(III) Studies showing how added empirical evidence changed the process understanding and helped to revise model structures & parameterisations
(IV) Studies addressing scaling of processes in models

We are happy to announce John Pomeroy (University of Saskatchewan) and Björn Guse (GFZ Potsdam) as confirmed invited speakers for this session.