HS2.2.4
From observations to models - journey of model development
Convener: Shervan Gharari | Co-conveners: Björn Guse, Sina Khatami, Charles Luce, Luis Samaniego, Simon Stisen
Orals
| Fri, 12 Apr, 10:45–12:30, 14:00–15:45, 16:15–18:00
 
Room C
Posters
| Attendance Fri, 12 Apr, 08:30–10:15
 
Hall A

Invited speakers:

Luca Brocca from National Research Council, Research Institute for Geo-Hydrological Protection, Perugia, Italy, with the title "The missing information for hydrological modelling in agricultural areas: irrigation"

Martyn Clark from University of Saskatchewan, with the title "Modeling spatial patterns in hydrology: Neglected challenges."

Session Description: Hydrological models are formulations of hypotheses about natural systems' behavior. These formulations are constructed and refined to maximize the model fidelity, i.e., the agreement of the model with the reality. Models’ formulations (e.g., parameterizations) and set ups are based on both observations and qualitative expert knowledge encoded by means of mathematical or statistical tools. The interaction between data availability, expert knowledge and set of decisions that result in a working model is an important topic of discussion in scientific hydrological modeling. In this session, we welcome contributions which elaborate on the interaction between observations, expert knowledge and models with the aim of improving process understanding and the realism of our environmental models.

Potential contributions may include (but not limited to): (1) improving model structural adequacy given data and expert knowledge, (2) introducing new formulations for model components (constitutive functions) capturing the internal and external model fluxes or their overall behavior, (3) upscaling and applying the experimentalists' knowledge at catchment, basin or global scale, (4) investigating the added value of new sources of data, i.e., remotely sensed products, and new model set up or formulation to accommodate them, (5) novel methods that use the new sources of data to constrain or evaluate models, (6) better representation of often neglected processes in hydrological models such as human impacts, river regulations, irrigation, as well as vegetation dynamics, (7) better monitoring and seamless modeling of spatial patterns in hydrological and land surface models using hyper-resolution distributed earth observations, (8) identification and quantification of driving forces that generate spatial patters in these models, (9) and development of novel regionalization/regularization approaches and performance metrics for matching simulated hydrological states and fluxes with spatio-temporal data sources.

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