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HS2.1.6

Process understanding in models - Improving hydrologic realism and reducing model weaknesses
Convener: Björn Guse  | Co-Conveners: Shervan Gharari , Charles Luce , Martyn Clark 
Orals
 / Wed, 11 Apr, 08:30–12:00  / Room B
Posters
 / Attendance Wed, 11 Apr, 17:30–19:00  / Hall A
Hydrological models comprise combinations of hypotheses about natural system behaviors. Hydrologists generate these formulations with the intent of maximizing model realism, i.e., the agreement of model predictions with observations. Though guided by theory and experience, there is an irony: attempts to improve model realism by including more details and modelled processes can come at the cost of increasing predictive uncertainty.

One contributing cause for such behavior is an inadequate theoretical foundation in some portion of a model, and figuring out which parts are sound and which are inconsistent requires rigorous evaluation and creative work with models. This session is dedicated to efforts to perform this work. A range of methods and approaches are being applied to improve models and hydrologic knowledge along with them.

This session invites contributions that (but not limited to):

(1) provide theories that can support hydrologic model development,

(2) improve the implementation of hydrological stores and fluxes (and their space-time variability) that are not currently adequately incorporated in models,

(3) use hydrological knowledge for an improved understanding of processes and patterns and how they can incorporated in models,

(4) investigate the added value of any newly available large data sets and any new model formulation,

(5) evaluate competing theories and model alternatives in presence of highly uncertain observed data,

(6) present suitable diagnostic metrics to accurately represent individual hydrological or ecological processes and to constrain model behaviour,

(7) increase hydrological consistency on model simulations to increase confidence in model predictions.

The intention of this session is to elicit a consistent understanding of model weaknesses, to prioritize needs for future model development, and to provide methods for generating more realistic process representations in models.

This session is organized as part of the grass-root modelling initiative on "Improving the Theoretical Underpinnings of Hydrologic Models" launched in 2016.

Invited speaker: Erkan Istanbulluoglu