Large scale evaluation of QPE, QPN and QPF improvements in a flash flood nowcasting framework with data assimilation

• Applicant: Professor Dr. Stefan J. Kollet, since 7/2022
• Subject Area: Hydrogeology, Hydrology, Limnology, Urban Water Management, Water Chemistry, Integrated Water Resources Management
• Term: since 2018
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 320397309

Nowcasting of river discharge and flash floods constitutes a major challenge, partly because operational NWP is not yet capable of predicting convective precipitation events at the sub-km and hourly scale in a useful quality. This leads to unforeseen flash floods resulting in large damages to public property and infrastructure, and potentially loss of life. Prominent examples in the area of the Geoverbund ABC/J are the destructive flash floods in Wachtberg on 3 July 2010 and on 6 June 2016. The project will develop a novel probabilistic nowcasting framework for river discharge and flash floods in small watersheds (<500km2). The project focuses on three well instrumented small headwater catchments of the Wachtberg, Ammer and Bode watersheds, prone to flash floods. We will employ QPE, QPN and QPF (Quantitative Precipitation Estimation, Nowcasting and Forecasting, respectively) developed by P1, P2 and P3 in a nowcasting framework for river discharge in order to assess the impact of the improved products on flash flood prediction. One of the original features of the project will be the application of different hydrological models (conceptual and physically-based) with data assimilation (discharge and soil moisture) for flash flood forecasting. We will identify the added value and limitation of each model (and data assimilation method) for this exercise. While conceptual models can benefit from the calibration of their parameters to best fit the main variable of interest (discharge) according to the application (e.g. high flows) and the possibility of quickly running larger ensembles, physically-based models can benefit from the increasing availability of observations and more detailed process and land cover descriptions, which make these models easily transferable to other catchments. We will ultimately investigate if these divergent approaches could provide complementary information for forecasting flash floods.

• DFG Programme: Research Units
• Subproject of: FOR 2589: Near-Realtime Quantitative Precipitation Estimation and Prediction (RealPEP)
• Co-Investigator: Professor Dr. Harrie-Jan Hendricks-Franssen
• Ehemalige Antragstellerin: Dr.-Ing. Carina Furusho, Ph.D., until 6/2022