Quantifying rainfall forecast uncertainty and error propagation in flash flood and landslide prediction models

Abstract

Extreme weather situations are becoming increasingly frequent with devastating consequences worldwide. Heavy rainfall events in July 2021 caused severe flash floods in western Germany, Belgium and the Netherlands, resulting in a high number of casualties and material damage. The high hazard potential combined with the low reaction times, associated with these events, make it necessary to develop efficient and reliable early warning systems (EWSs) to facilitate the preparation of response strategies. As nowcast precipitation forecasts are continuously improving in both quality and spatial resolution, they become an essential input for flash flood and landslide prediction models and therefore an important component in EWSs. However, the inherent uncertainty of radar-based nowcasting systems are carried over to the output of those prediction models. Therefore, this study aims to analyze the uncertainty sources of nowcasting products of the German weather service (DWD) using the July flood Event 2021 as a case study. More specifically, the objective is to determine whether the quality of precipitation nowcast products is sufficient for usage in physics-based flood or landslide prediction models. Due to the complex nature of weather and rainfall structures as well as their spatio-temporal variability, traditional cell-by-cell comparison of predictions and ground truth is insufficient to quantify forecast quality. To overcome this issue, uncertainties in magnitude, time and space and their respective sources are identified, using techniques from various fields of science. Subsequently, error propagation in flash flood prediction models is analyzed by applying the previously determined uncertainty ranges to a hydrological model.

Authors 6

1. Bastian Winkels Aachen Institute of Hydraulic Engineering and Water Resources Management Methods for Model–based Development in Computational Engineering

   RWTH Aachen University

   Affiliation as printed

   Institute of Hydraulic Engineering and Water Resources Management, RWTH Aachen University, Aachen, 52062, Germany

   Methods for Model-based Development in Computational Engineering, RWTH Aachen University, Aachen, 52062, Germany

2. Julian Hofmann corresponding Aachen Institute of Hydraulic Engineering and Water Resources Management

   RWTH Aachen University

   Affiliation as printed

   Institute of Hydraulic Engineering and Water Resources Management, RWTH Aachen University, Aachen, 52062, Germany

3. Anil Yıldiz corresponding Aachen Methods for Model–based Development in Computational Engineering

   RWTH Aachen University

   Affiliation as printed

   Methods for Model-based Development in Computational Engineering, RWTH Aachen University, Aachen, 52062, Germany

4. Ann-Kathrin Edrich Aachen AICES Graduate School Methods for Model–based Development in Computational Engineering

   Aachen Institute for Advanced Study in Computational Engineering Science · RWTH Aachen University

   Affiliation as printed

   AICES Graduate School, RWTH Aachen University, Aachen, 52062, Germany

   Methods for Model-based Development in Computational Engineering, RWTH Aachen University, Aachen, 52062, Germany

5. Holger Schüttrumpf Aachen Institute of Hydraulic Engineering and Water Resources Management

   RWTH Aachen University

   Affiliation as printed

   Institute of Hydraulic Engineering and Water Resources Management, RWTH Aachen University, Aachen, 52062, Germany

6. Julia Kowalski Aachen Methods for Model–based Development in Computational Engineering

   RWTH Aachen University

   Affiliation as printed

   Methods for Model-based Development in Computational Engineering, RWTH Aachen University, Aachen, 52062, Germany