The presented paper deals with the numerical modeling of groundwater response to the extreme hydrological situations in the Danube River. A 3-D numerical groundwater modeling is carried out using MODFLOW (McDonald and Harbaugh, 1998) and Groundwater Modeling System (AQUAVEO, 2021) simulation packages for available hydrological, geological, and hydro-geological parameters to study how the groundwater responded to the flood event in the Danube River that occurred in June 2013.

<p>A well-configured, verified hydrological operational forecasting system is an invaluable tool for hydrological forecasting and warning services. Target users of such a service can be water managers, power generation planning, navigation, civil protection, and the public, whose priority is to obtain the best possible forecast for their area of interest. This was one of the reasons why SHMU proceeded to a more complex assessment of hydrological forecasts.</p> <p>The main objective of the assessment was to analyse the uncertainties that significantly affect the quality of the forecast itself. The evaluation was conducted for 47 selected water-gauging profiles. It showed that in Slovak physical-geographical conditions, the precipitation data (measured and predicted) and the configuration of the hydrological model are the most significant sources of uncertainties. Forcing data for hydrological forecasts come from the deterministic ALADIN/SHMU model with 4.5 km resolution, generated 4 times per day with hourly time-step and lead time 69 hours. The HBV model efficiency was tested on a total of 138 forecast profiles during the period 08/2016 – 12/2020. The input data used was precipitation from a combined radar product (qPrec) with 1 km resolution, which also enters the models in operation. Model performance was expressed by NSE and KGE statistics as well as visual inspection of the hydrographs. It showed very good model simulation results for most of the catchments. A weak point was the simulation and forecast of peak flows, which the model underestimated in many cases. It was therefore necessary to proceed to a more detailed analysis of the precipitation input, both measured and predicted, in relation to the predicted flows. Monthly precipitation totals and for selected catchments also daily ones were analysed and feedback was sent to the precipitation data providers for hydrological models. Monthly precipitation totals were compared with totals obtained from spatial interpolation of 568 rain gauge stations in a GIS environment. From these comparisons, systematic errors are visible as well as their temporal evolution for the specific catchments. Such analyses are not a routine part of hydrological forecasting systems.</p> <p>The work also includes a quantification of the uncertainty of the meteorological forecast and hydrological model separately expressed for different forecast lead times for a specific forecast profile. In the future, we would like to apply the methodology used for other profiles in order to detect possible systematic errors affecting the quality of the hydrological forecast.</p> <p>This work was supported by the Slovak Research and Development Agency under the Contract no. APVV-19-0340.</p>

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