## 3 Results
### QPE Improvement
#### 3.2.2 Hydrological Modelling  
As mentioned before, one of the most effective ways to evaluate the performance of an improved QI-based QPE is to verify it through different weather forecasting, nowcasting, or hydrological models. We also carried out such a test, by feeding the outputs of the _qPrec_ software as inputs in the hydrological model HBV (Hydrologiska Byrans Vattenbalans, Hydrological Bureau's Water Balance [30]), which is, among others, operationally used by the hydrological forecasters of the SHMU and hydrological experts of MicroStep-MIS. Figure 7 presents a comparison of three series of daily discharges for a selected 12-month period (1 November 2016 to 1 November 2017) for the Hron River at the gauging station Polomka (630 m a.s.l., Central Slovakia; the area of the upstream basin 329.54 km\({}^{2}\)) as the observed one, and two further series as a result of hydrological modelling on the precipitation estimation by the _qPrec_ software and the INCA model (Integrated Nowcasting through Comprehensive Analysis [31]), respectively. \begin{table}
\begin{tabular}{c c c c} \hline
**Radar/Gauge Ratio** & **Marshall–Palmer** & **Calibration,** & **Calibration,** \\ \(r_{RG}\) [–] & **[\%]** & **no QI [\%]** & **with QI [\%]** \\ \hline \(r_{RG}<0.5\) & 0.0 & \(17.1\) & 0.5 \\ \(0.5<r_{RG}\leq 0.8\) & 1.9 & 38.5 & 22.4 \\ \(0.8<r_{RG}\leq 1.2\) & 14.9 & 40.2 & 71.6 \\ \(1.2<r_{RG}\leq 1.5\) & 27.9 & 3.7 & 5.1 \\ \(1.5<r_{RG}\leq 2.0\) & 42.5 & 0.5 & 0.4 \\ \(r_{RG}>2.0\) & 12.8 & 0.0 & 0.0 \\ \hline \end{tabular}
\end{table} 
Table 1: Summary of the frequency of the occurrence of sites (in %) with a given radar/gauge ratio \(r_{RG}\) in three maps of Figure 6. Based on the network of 570 pluviometric stations. In the hilly and mountainous regions of Slovakia (such as the Hron River at Polomka), the largest discharges are observed either due to snowmelt during the late spring months (April-May) or due to convective rainfall or stratiform precipitation during the summer or autumn months. Both effects are clearly discernible in Figure 7: (i) the increased discharge values due to the heavy snowmelt around May 1 where the corresponding flood wave attenuated slowly and lasted for a couple of weeks, and (ii) the shorter and quicker flood events in the warm half year. Figure 7 further shows that the outputs of the hydrological model reflect these phenomena in a different way. Both the _qPrec_- and the INCA-based results were able to follow the course of the observed discharge (also with the influence of partial snowmelt) during the cold half year acceptably well. Significant differences in the model behavior appeared in the warm half year where the connection between the precipitation and the discharge was more straightforward. The _qPrec_-based hydrograph copied the behavior of the observed discharges both in terms of timing and magnitude (with minor underestimation), whereas the INCA-based outputs constantly and significantly overestimated the real-world values. The bar plot in Figure 8 explains the findings derived from the hydrographs. The differences in the outputs of hydrological modelling stem in discernible differences in the time series of 1-h area-averaged rainfall in the upstream basin: the INCA-based rainfall estimates generally exceed the _qPrec_ values, particularly in the period starting from May. Due to the fact that there is only a single meteorological observatory in the given basin, a comparison of the INCA and _qPrec_ estimates with the gauge data is omitted. Figure 8: Time series of 1-h area-averaged rainfall rates (INCA vs. _qPrec_ estimates) in the Polomka basin at the Hron River, from 1 November 2016 to 1 November 2017. Figure 7: Course of the discharge values with an hourly time step for the Hron River at Polomka (Central Slovakia) from 1 November 2016 to 1 November 2017. The observed values are displayed in green, whereas the red (blue) color indicates the estimated discharge from the _qPrec_ software (model INCA—Integrated Nowcasting through Comprehensive Analysis [31]).