Uncertainty Assessment of water flow and nutrient loads under future climate change conditions

UnLoadC³ aims at developing and applying an extended uncertainty estimation framework for water quantity and quality (N, P) modelling under climate change conditions. First, a new set of regional climate change scenarios on a finest possible grid for Austria will be generated, considering a much wider range of emission, GCM/RCM and statistical downscaling scenarios than currently available. Considering input data -, model structural -, model parameter - and output/calibration data - uncertainties in an ensemble-based Bayesian uncertainty estimation framework will allow a much wider range of possible future outcomes and the individual contribution of each uncertainty to be analysed in detail. This will strongly support policy makers and water managers to consider and prioritise adaptation and mitigation activities.