The basis of an early warning systems are observations and models. Observations give direct information about current conditions. How high are the water levels? Is there a large snow pack? However, observations do not give answers to questions related about the future, (will the water level reach flood level?) or about question related to system functioning: does the snow pack and high temperatures mean that there is a flood risk?
Fig. 1: Nant de Drance Pumped Storage plant (Marti Tunnel AG, 2020)
Figure 2: The basics of an early warning system: observation and forecast
For these questions we need modelling. This modelling consists of many aspects. For the FLOMRESPONS project, SINTEF and Deltares have set-up a base modelling system, however there is still much to be improved.
The topic of this MSc thesis is to identify where the current modelling can be improved, related to:
- Optimizing the hydrological model to the local conditions
- Pre-processing meteo forecasts for model input
- Post-processing ensemble streamflow forecasts
To get a general idea on pre- and postprocessing this paper is relevant for the Norwegian context: https://hess.copernicus.org/preprints/hess-2021-13/