EGU24-21875, updated on 11 Mar 2024
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Modelling the impact of antecedent conditions on flood forecasting

Dimosthenis Tsaknias and Dapeng Yu
Dimosthenis Tsaknias and Dapeng Yu
  • Loughborough University, Geography and Environment, Loughborough, United Kingdom

Antecedent conditions play a crucial role in flooding, and hence it is essential to simulate them when floods are forecasted. Wet antecedent conditions can lead to significant flooding even if the rainfall during an event is not very intense, prolonged or widespread. An example of this type of flooding is the European floods in the summer of 2013, which affected Germany, Czech Republic and Austria; leading to 25 fatalities and financial losses amounting to 16 billion USD (Munich Re, 2013).

This study presents a modelling framework aimed focusing on the interplay between antecedent conditions and flood events. Our approach integrates a new component related to antecedent conditions to Previsico’s proprietary FloodMap Live by leveraging geospatial datasets as well as past precipitation data. The ground parameters are modified automatically without the need of manual intervention.

In this study we discuss the data processing spatially and temporally, and the impact of antecedent conditions for various events by showcasing different scenarios in the United Kingdom. Moreover, we investigate the model sensitivity and performance when compared with observation points which were flooded.

This research investigates the importance of antecedent conditions on flood modelling and  contributes to our understanding of how scenario-based events should be modelled in order to improve forecast performance. These improvements improve the accuracy of Previsico’s flood forecasts as they add a new component related to how the ground conditions changed a few days before a flood event.


Munich Re, 2013. Floods dominate natural catastrophe statistics in first half of 2013. Available at:


How to cite: Tsaknias, D. and Yu, D.: Modelling the impact of antecedent conditions on flood forecasting, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21875,, 2024.