Uncertainty assessment of water flow and nutrient loads under fututre 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 un-certainty to be analysed in detail. This will strongly support policy makers and water managers to consider and prioritise ad-aptation and mitigation activities.