EGU24-7372, updated on 08 Mar 2024
https://doi.org/10.5194/egusphere-egu24-7372
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Operational Hydrological Ensemble Forecasts in Small Catchments – Implementing Seamless Precipitation Predictions

Michael Wagner and Jens Grundmann
Michael Wagner and Jens Grundmann
  • TU Dresden, Institute of Hydrology and Meteorology, Chair of Hydrology, Dresden, Germany (michael.wagner@tu-dresden.de)

Runoff in small catchments tend to response quickly to heavy precipitation input. The potential disastrous consequences demand a reliable precipitation forecast and flood early warning for an appropriate flood defense management. Numerical weather models provide relatively long lead times that allow early warnings of heavy precipitation. Further, meteorological ensembles consider the uncertainty of the forecast. Feeding this data to a hydrological model propagates the meteorological information and its uncertainty to catchment discharge time series.

Within the scope of the project HoWa-PRO (funded by the Federal Ministry of Education and Research, Germany) we propose a flood early warning system for the example of three catchments in the Free State of Saxony. The so-called sentinel watches meteorological ensemble forecasts of the German Weather Service (DWD). If a specific precipitation criterion is surpassed, the sentinel starts collecting and concatenating various precipitation products. For operational use, a combination of radar, nowcast, and (ensemble) forecast data is created (Radolan-RW, Radolan-RV, Icon-D2-EPS, Icon-EU). Besides this renowned precipitation products, we set up a second hydrologic ensemble forecasting system using prototypic data of upcoming products for precipitation observation and forecasting. Here we combine (1) observed radar data assimilated to precipitation gauges and commercial microwave links (pyRADMAN), and (2) the seamless prediction data SINFONY-INTENSE. The latter is a combination of nowcasting and numerical forecast ensembles. Both data products are delivered some minutes earlier than the classic data. The sentinel evaluates the concatenated precipitation data in the catchments according to further criteria for heavy precipitation events. If a criterion is met, the hydrological model is started with the formerly concatenated full ensemble precipitation data. The results are used in a prototypic web demonstrator to depict the current flood situation in the covered catchments. An easy to grasp traffic light scheme and – if needed or wanted – additional information including the uncertainty range facilitate quick decisions and actions of the flood defense management in the appropriate region.

The sentinel scales well with additional catchments which can be simulated in parallel. Currently, the sentinels for both data versions (operational and upcoming precipitation products) are invoked each 30 min, shortly after new observed data is delivered. The used WeatherDataHarmonizer library (Wagner and Grundmann, 2023) ensures a temporally, spatially, and formally homogeneous precipitation data set with a lead time of maximum 180 h, a time resolution of 15 min, and a spatial resolution of about 1 km. Each component of the sentinel is robust in a sense of handling missing operational data or machine faults.

Additionally to the technical aspects, we present results of operational hydrologic ensemble forecasts for selected events and catchments and compare the performance of both systems.

Wagner, M. and Grundmann, J.: Precipitation Data Harmonizer: Harmonizing radar, nowcast, and forecast precipitation data for hydrological applications, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-8978, https://doi.org/10.5194/egusphere-egu23-8978, 2023.

How to cite: Wagner, M. and Grundmann, J.: Operational Hydrological Ensemble Forecasts in Small Catchments – Implementing Seamless Precipitation Predictions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7372, https://doi.org/10.5194/egusphere-egu24-7372, 2024.