EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Using radar-derived precipitation data for hydrological modelling in selected study sides in Norway

Jessica Sienel1,2, Lennart Schönfelder1, and Jochen Seidel2
Jessica Sienel et al.
  • 1SINTEF Energy Research, Energy Systems, Norway
  • 2Institute for Modelling Hydraulic and Environmental Systems, University of Stuttgart, Germany

Gathering accurate precipitation data is an important task for setting up hydrological models. In Norway, the gauge network density is higher in the southern parts and decreases in the north. Furthermore, the amount of high evaluated precipitation gauges is rather scarce. Radar data is available but lacks an accurate reflectivity-precipitation relation and errors in precipitation estimation are caused for example by beam blockage.

For modelling purposes, this study aims to evaluate whether the application of radar derived data gives any benefit, especially when modelling in a higher temporal resolution. The results of this study can give decision support for modellers having difficulties choosing the precipitation product. For that cause, spatial interpolated precipitation products were evaluated and compared in terms of performance in hydrological models. The Meteorological Institute Norway publishes gridded hourly datasets covering the Norwegian mainland: seNorge2, where gauge data is interpolated using an optimal interpolation, and the numerical weather prediction product (NWP), a combination of gauge data, radar data and a numerical weather model. Five different catchments were simulated in the numerical precipitation-runoff model HYPE with both datasets for comparison. The catchments vary in area, hydrological regime and availability of nearby gauges. The simulation was done in an hourly time step in order to compare precipitation variability on a small time scale.

In this study, a calibration method was developed that generates comparable and stable performance results in terms of the Kling–Gupta efficiency (KGE) for each catchment and dataset. The resulting discharges and water balances of the catchments were analysed and compared. Additionally, selected precipitation events, where the precipitation products were not able to describe atmospheric processes appropriately, were analysed. The datasets were further compared by spatially accumulating annual precipitation sums over the catchments, by using a private weather station to evaluate the fit of the data and by comparing the runoff and precipitation volume of the basins.

Preliminary results show the significant differences in water volume and spatial distribution of precipitation between these products. Furthermore, when comparing a private gauge with the precipitation products at an ungauged area, daily precipitation data tends to be more accurate than hourly data.

How to cite: Sienel, J., Schönfelder, L., and Seidel, J.: Using radar-derived precipitation data for hydrological modelling in selected study sides in Norway, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8119,, 2022.


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