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Advances in Diagnostics, Sensitivity, and Uncertainty Analysis of Earth and Environmental Systems Models
Convener: Amin Haghnegahdar  | Co-Conveners: Wolfgang Nowak , Cristina Prieto , Hoshin Gupta , William Becker , Saman Razavi , Thomas Wöhling 
 / Mon, 09 Apr, 08:30–12:00  / 13:30–15:00
 / Attendance Mon, 09 Apr, 17:30–19:00

Highlight: We are delighted to have Dr. Martyn Clark (WRR Editor-in-Chief) as the invited speaker in our session.

Proper characterization of uncertainty remains a major challenge, and is inherent to many aspects of modelling such as structural development, hypothesis testing and parameter estimation, and the adequate characterization of forcing data and initial and boundary conditions. To address this challenge, methods for a) uncertainty analysis (UA) that seek to quantify uncertainty (and how it propagates through a system/model), and b) the closely-related methods for sensitivity analysis (SA) that evaluate the role and significance of uncertain factors (in the functioning of systems/models), have proved to be very helpful.
This session invites contributions that discuss advances, both in theory and/or application, in methods for SA/UA applicable to all Earth and Environmental Systems Models (EESMs). This includes all areas of hydrology, such as classical hydrology, subsurface hydrology and soil science. Topics of interest include (but are not limited to):

1) Novel methods for effective characterization of sensitivity and uncertainty
2) Single- versus Multi-criteria SA/UA
3) Novel methods for spatial and temporal evaluation/analysis of models
4) The role of data information and error on SA/UA (e.g., input/output error, model structure error, etc.)
5) Novel approaches and benchmarking efforts for parameter estimation and data inversion
6) Improving the computational efficiency of SA/UA (efficient sampling, surrogate modelling, parallel computing, model pre-emption, etc.)

Contributions addressing any or all aspects of sensitivity/uncertainty, including those related to structural development, hypothesis testing, parameter estimation, forcing data, and initial and boundary conditions are invited.