Evaluating fluvial flood mapping for flood early warning, Ry River Denmark

Until recently, flood early warning in Denmark was based on weather and marine forecasting for extreme rainfall and sea water levels. In 2022, the Danish Meteorological Institute (DMI) was appointed as the national authority for flood forecasting for Denmark, and was tasked with developing and implementing a national flood forecasting and early warning system. The initial goal for these developments was to provide timely, reliable and relevant data to support decision-making by local and national emergency services prior to major flood events.

Initial efforts were focused on the development of a rapid, nationwide flood extent mapping for addressing both pluvial flooding from intense summer cloudbursts and coastal flooding associated with elevated sea water levels and storm surges. In parallel, a national hydrological forecasting system has been successfully developed and the forecasted discharges now form the basis for fluvial flood early warning for the Danish emergency services (2024) and for the general public (2025). However, there remains a critical need for forecasts of flood extent, ahead of extreme events, along the river systems. The key challenge is to deliver flood extent forecasts with sufficient lead time and reliability to support decision-making by authorities during time-critical emergency situations.

In this study, we explore the trade-off between computationally efficient but approximate methods against more accurate but computationally more demanding hydrodynamic simulations for the case study area Ry River (Ryå). The Ryå catchment drains a relatively large – and low-gradient– area of 590 km², but drainage capacity has become increasingly constrained. This has become evident from prolonged and more frequent flooding of intensively cultivated agricultural areas. Ryå represents many of the river modelling and forecasting cases in Denmark but is particularly challenging because of the low slopes.

In particular, we compare and evaluate three methods of varying complexity for estimating flood extent. These are, in order of increasing complexity: 1. GIS-based, static mapping from measured or simulated water levels, 2) an approximate 1D-2D hydrodynamic coupled model obtained by simplifying the governing (St. Venant) equations (LISFLOOD-FP) and 3) a full 2D hydrodynamic modelling of the river and floodplains (HEC-RAS). Performance comparisons, for selected flood events during 2019-2024, are carried out using optical drone imagery together with both radar-based and optical satellite data. We evaluate model run time and accuracy and in the end also the usefulness of the tools to build models covering larger areas of Denmark and being run on-demand. The goal is to determine which methods can, with sufficient accuracy, be used in a semi-operational manner in DMI’s warning setup.