The quality of meteorological forecasts is constantly improving through advances to meteorological models and the ability to assimilate data into the models. Seasonal predictions that look 4-6 months into the future are inherently more uncertain than short-term forecast for the coming days. Nevertheless, recent studies indicate that despite these uncertainties, seasonal forecast are now of a quality that can help optimize planning and allocation of water usage.
Project type: R&D
Place: Funen, Denmark
Partners: Aarhus University and WATExR project partners
Funder: JPI Climate
There are no operational workflows where seasonal weather predictions are used by impact models to allow easy access to seasonal predictions for hydrology and water quality.
In this project, WaterITech developed a software workflow that allowed an ensemble of seasonal weather predictions to be run through a coupled, open-source, watershed-lake model complex based on the SWAT and GOTM-WET models, respectively.
Ensemble simulations enable quantification of the uncertainty in the predicted hydrological and water quality responses, which can be an important factor if using these predictions for decision making.