S10

Forecasting and making decisions under uncertainty: ensemble approaches, evaluation methods and lessons learnt from post-event analyses
Convener: Shaun Harrigan | Co-Conveners: James Bennett, Marie-Amélie Boucher, Céline Cattoën-Gilbert, Fernando Mainardi Fan, Ilias Pechlivanidis, Maria-Helena Ramos, Paolo Reggiani

Forecasting plays a key role in decision making. This may concern users dealing with both risk assessment of extremes (floods, droughts) and water resources management, and involves several scales in time (hours to weeks or months ahead) and space (global to local forecasts). A large number of operational applications may benefit from hydrological forecasting systems that include uncertainty quantification and issue reliable and accurate forecasts.
This session explores the interconnections between ensemble hydro-meteorological forecast techniques and decision making under uncertainty, with applications such as (but not limited to) communication of flood warning, drought risk assessment, reservoir control and operation planning, water use planning among multiple users, hydropower production, fluvial transportation, agricultural and food production management.
Contributions are particularly welcome on:
• understanding and quantifying sources of uncertainty and predictability for decision-making;
• real-time (or near real-time) approaches for ensemble data assimilation, NWP preprocessing, seamless forecasting, multi-model combinations, sub-selection of ensemble sets and hydrological post-processing;
• the challenges of effective communication of hydrometeorological forecasts and the visualisation of their uncertainty and skill;
• the challenges of transferring science into operational practices;
• improving the engagement of users in the definition and development of novel operational forecasts products and services;
• verification of ensemble forecasts, in particular methods tailored to decision makers.
• The session is organized under the auspices of the HEPEX (www.hepex.org) initiative, which brings together a community of practice in hydrological ensemble predictions to foster scientific developments necessary to improve the skill of probabilistic hydrological predictions and their use in operational contexts.