Please note that this session was withdrawn and is no longer available in the respective programme. This withdrawal might have been the result of a merge with another session.
ITS1.17/SSS0.1.3 | Quantifying and communicating uncertainty in environmental geoinformation derived from measurements, process models, and machine learning
EDI
Quantifying and communicating uncertainty in environmental geoinformation derived from measurements, process models, and machine learning
Convener: Madlene NussbaumECSECS | Co-conveners: Christopher ChagumairaECSECS, Gerard Heuvelink, Mareike Ließ, Alexandre Wadoux
In complex environmental systems, uncertain information (whether in measurements, maps or models) is the norm, and this impinges on most knowledge that earth scientists generate. Accounting for this uncertainty is particularly important when results are used in a decision-making process where the end user needs to be able to properly evaluate the risks involved.

The transdisciplinary challenge of quantifying and communicating uncertainty requires continuous improvement of tools. This concerns the quantification of uncertainty associated with measurement data and expert information, its propagation through any modelling procedure (machine learning, geostatistics, process models, …), as well as the visualization and communication of uncertainty to the end users including scientists, engineers, policymakers, and the general public.

In this session, we will examine the state of the art, and discuss fascinating advances of both uncertainty quantification, and communication in earth and environmental sciences. We welcome submissions on three components of the research field: 1) new methods and applications of uncertainty quantification; 2) use of uncertain information in decision-making, and for risk assessment; and 3) efficient and effective communication and visualization of uncertainty to end-users. It takes expertise from several different disciplines (including earth and environmental sciences, statistics, economics, and psychology) to successfully include, manage, and communicate uncertainty.