Symposium on Uncertainty Quantification in Computational Geosciences

Uncertainty Quantification

Modelling activities are steadily increasing in all disciplines of geosciences, ranging from natural resources exploitation to environmental and natural hazard assessments. Advances in research and computing makes it possible to run more complex and more accurate computational models such as high-fidelity full process-based numerical models  It provides accurate simulations of physical processes which are, in return, more costly to evaluate and validate Uncertainty Quantification (UQ) is now widely used in diverse aspects of the modelling  (e.g. model development, calibration and validation, decision-making, etc.) and is inherent to many disciplines encountered in computational geosciences including earthquake, fluvial or coastal flood, landslides, volcanoes, underground water resources, mineral exploitation, etc.. Despite the ever-increasing computing power, a proper UQ is still a major challenge. Over the last years, a large variety of methodological developments have been proposed for in order to improve confidence in simulation results, to help decision-making under uncertainty, and to facilitate communication to stakeholders. It has led to the integration of ideas from multiple communities: mathematics, statistics, geology, geophysics, geography, climatology, hydrology, etc.

The objective of the symposium is to bring together and to promote interchange between a diverse community of research scientists, students, practitioners and stakeholders concerned with this complex and inter-disciplinary topic. The symposium will provide a forum for the exchange of experiences / feedbacks and new fruitful perspectives for the coming years on UQ in Computational Geosciences through thematic sessions and panel discussions. This symposium will be organized for 2 days with a special focus on the applicability and on the successes (or failures) of UQ methods applied to four domains of Geosciences, namely:

  1. UQ applied to natural risks related to geological processes
  2. UQ applied to hydro-meteorological processes
  3. UQ applied to natural resources (water and mineral) exploration and exploitation
  4. Methods and theoretical developments for UQ

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