1EMVIS S.A., Consultant Engineers-Environmental Services, Research Information Technology & Services, 15343 Athens, Greece
2National Technical University of Athens, Department of Water Resources and Environmental Engineering, School of Civil Engineering, 15780 Athens, Greece
3Technische Universität Braunschweig, Leichtweiß-Institute for Hydraulic Engineering and Water Resources, Division of Hydrology and River Basin Management, Germany
4University of Ljubljana, Faculty of Civil and Geodetic Engineering, Jamova cesta 2, Ljubljana, Slovenia
previously published under the name Hannes Müller
1EMVIS S.A., Consultant Engineers-Environmental Services, Research Information Technology & Services, 15343 Athens, Greece
2National Technical University of Athens, Department of Water Resources and Environmental Engineering, School of Civil Engineering, 15780 Athens, Greece
3Technische Universität Braunschweig, Leichtweiß-Institute for Hydraulic Engineering and Water Resources, Division of Hydrology and River Basin Management, Germany
4University of Ljubljana, Faculty of Civil and Geodetic Engineering, Jamova cesta 2, Ljubljana, Slovenia
Received: 16 Nov 2022 – Discussion started: 06 Dec 2022
Abstract. Observational data scarcity often limits the potential of rainfall-runoff modelling around the globe. In ungauged catchments, earth-observations or reanalysis products could be used to replace missing ground-based station data. However, performance of different datasets needs to be thoroughly tested, especially at finer temporal resolutions such as hourly time steps. This study evaluates the performance of ERA5-Land and COSMO-REA6 precipitation reanalysis products (PRPs) using 16 meso-scale catchments located in Slovenia, Europe. These two PRPs are firstly compared with a gridded precipitation dataset that was constructed based on ground observational data. Secondly, a comparison of the temperature data of these reanalysis products with station-based air temperature data is conducted. Thirdly, several data combinations are defined and used as input for the rainfall-runoff modelling using the GR4H model. A special focus is on the application of an additional snow module. Both tested PRPs underestimate, for at least 20 %, extreme rainfall events that are the driving force of natural hazards such as floods. In terms of air temperature both tested reanalysis products show similar deviations from the observational dataset that was catchment-specific. Additionally, air temperature deviations are smaller in winter compared to summer. In terms of rainfall-runoff modelling, the ERA5-Land yields slightly better performance than COSMO-REA6. If a re-calibration with PRP has been carried out, the performance is similar compared to the simulations where station-based data was used as input. Model recalibration proves to be essential in providing relatively sufficient rainfall-runoff modelling results. Hence, tested PRPs could be used as an alternative to the station-based based data in case that precipitation or air temperature data are lacking, but model calibration using discharge data would be needed to improve the performance.
I have read the manuscript entitled " Validation of precipitation reanalysis products for rainfall-runoff modeling in Slovenia", which is a comparative analysis of two reanalysis precipitation datasets, ERA5-Land and COSMO-ERA6, to runoff simulation over different regions of Slovenia
the manuscript is relatively interesting and well written. I consider that it is suitable for publication in the EGUsphere journal, although, I would like to give some comments to the authors for the general improvement of the manuscript.
1- Please use more recent papers that are relevant to your topic. Below you can find some new studies:
2- Improve the quality of all figures. For example, in Fig1, 2, texts and numbers are blurred and need to improve.
3- What are your criteria for mesoscale, large-scale, and microscale categories?
4- Some of the studied catchments have an Area value lower than 100 km2, While ERA5-Land cells are higher than 100 km2. How did you deal with this issue? I think using this dataset for small catchments is not suitable. However, Still I don't understand your criteria for mesoscale. these catchments fall in the microscale category.
5- The values of numbers in Table 3 are not clear and I can't check the dataset combinations.
6- The authors used the GR4H model for runoff simulation. Based on the model structure (Fig 4), this model doesn't consider the snow component through the modeling. How do you explain this issue for snowy catchments of Slovenia?
7- For precipitation comparison, which approach is used in this study? Point-scale or Grid-scale approach? However, Based on fig1 and fig3 the density of your ground-gauge observations is not so good.
8- It is recommended to plot stream flow time series for a better understanding of model performance for simulating peak and low flows.
9- For the estimation of ET, which formulas and datasets are used for running the GR4H model? Please clarify this issue in the revised paper.
10- Why didn't the authors consider the uncertainty analysis for using the GR4H model?
For the rainfall-runoff simulation from a certain area hydrological models are used, which require precipitation and temperature data as input. Since these are often not available as observations, we tested simulation results from atmospheric models. Two products were tested (ERA5-Land & COSMO-REA6) for Slovenian catchments, both lead to good simulations results. Their usage enables the of rainfall-runoff simulation in unobserved catchments as a requisite for e.g. flood protection measures.
For the rainfall-runoff simulation from a certain area hydrological models are used, which...
