Hydrological forecasting is of critical importance to support informed decisions for emergency response planning, flood management, drought mitigation and water resources planning. Forecasting models translate meteorological forecasts into estimates of key hydrological variables (i.e. discharge, water level, soil moisture, evapotranspiration) at various lead times and spatial resolution. There has been immense progress in real-time to short-term and seasonal forecasting by applying new techniques such as Machine Learning, quantifying the associated uncertainty in the modelling chain (forecast uncertainty), assimilating observed in-situ and satellite-based data into forecast model and the use of post-processing techniques to generate more accurate and reliable hydrological forecast products. This progress has improved the usefulness of hydrological forecasts for impact assessment, risk-based decisions, and eventually operational risk management. Yet, there is room for further investigation of new opportunities, challenges, and applications in this area.
This session invites contributions dealing with all aspects of hydrological forecasting such as:
Key topics: Hydrological modelling & forecasting, Flood inundation modelling & forecasting, Probabilistic (risk-based) impact assessment, Risk-based decision making /decision support