Torrential streams and fast runoff are characteristic of most Slovenian rivers and extensive damage is caused almost every year by rainstorms affecting different regions of Slovenia. Rainfall-runoff models which are tools for runoff calculation can be used for flood forecasting. In Slovenia, the lag time between rainfall and runoff is only a few hours and on-line data are used only for now-casting. Predicted precipitation is necessary in flood forecasting some days ahead. The ECMWF (European Centre for Medium-Range Weather Forecasts) model gives general forecasts several days ahead while more detailed precipitation data with the ALADIN/SI model are available for two days ahead. Combining the weather forecasts with the information on catchment conditions and a hydrological forecasting model can give advance warning of potential flooding notwithstanding a certain degree of uncertainty in using precipitation forecasts based on meteorological models. Analysis of the sensitivity of the hydrological model to the rainfall error has shown that the deviation in runoff is much larger than the rainfall deviation. Therefore, verification of predicted precipitation for large precipitation events was performed with the ECMWF model. Measured precipitation data were interpolated on a regular grid and compared with the results from the ECMWF model. The deviation in predicted precipitation from interpolated measurements is shown with the model bias resulting from the inability of the model to predict the precipitation correctly and a bias for horizontal resolution of the model and natural variability of precipitation.

The standard conceptual HBV model was originally developed with daily data and is normally operated on daily time step. But many floods in Slovenia are usually flash floods as result of intense frontal precipitation combined with orographic enhancement. Peak discharges are maintained only for hours or even minutes. To use the HBV model for flash flood forecasting, the version of HBV-96 has been applied on the catchment with complex topography with the time step of one hour. The recording raingauges giving hourly values of precipitation have been taken in calibration of the model. The uncertainty of simulated runoff is mainly the result of precipitation uncertainty associated with the mean areal precipitation and is higher for mountainous catchments. Therefore the influence of number of raingauges used to derive the areal precipitation by the method of Thiessen polygons was investigated. The quantification of hydrological uncertainty has been performed by analysis of sensitivity of the HBV model to error in precipitation input. The results show that an error of 10% in the amount of precipitation causes an error of 17% in the peak of flood wave. The polynomial equations showing the relationship between the errors in rainfall amounts and peak discharges were derived for two water stations on the Savinja catchment. Simulated discharges of half-yearly runs demonstrate the applicability of the HBV model for flash flood forecasting using the mesoscale meteorological forecasts of ALADIN/SI model as input precipitation data.

Drought is a complex phenomenon with high spatial and temporal variability. Water scarcity has become a growing problem in Slovenia in recent decades. Therefore, the spatial and temporal variability of hydrological drought was investigated in this study by analysing the Standardized Streamflow Index (SSI). Monthly discharge data series from 46 gauging stations for the period 1961–2016 were used to calculate SSI values at five different time scales (1, 3, 6, 12, and 24 months). The results indicate that the frequency and intensity of droughts in Slovenia has increased in recent decades at most of the analysed gauging stations and at all time scales considered. Spring and summer periods were identified as critical in terms of water deficit. SSI values vary independently from the location of the gauging station, confirming that drought is a regional phenomenon, even in a small country such as Slovenia. However, SSI values vary considerably depending on the time scale chosen. This was also confirmed by the results of the hierarchical clustering of the number of extreme droughts, as various time scales resulted in a different distribution of gauging stations by individual groups.

Intermittent watercourses lack water during some periods of the year, which especially applies to karst sinking streams. Droughts also occur in dry periods with no rainfall over a longer period of time. The drying up of Slovenian rivers was analysed using the data from the state hydrological monitoring of the Slovenian Environment Agency. By analysing the periodic statistics of minimum low discharges (nQnp), 18 gauging stations were extracted where the watercourses dried up during the measurement period. For these stations, sets of mean daily discharges were analysed, and dry days where the flow was equal to zero were listed. The number of dry days and the number of consecutive dry days were analysed by month and year, and the longest dry periods were determined. The results are presented graphically. At most of the gauging stations considered, the number of dry days was the highest in the years characterized by extreme hydrological droughts, namely 2003, 2012, and 1993. In some watercourses, drying up is a constant phenomenon that occurs almost every year, while others only dry up in years characterized by extreme droughts. Exceptions to this are the karst rivers, which sink and are therefore dry for part of the year. The Pivka and Branica Rivers regularly dry up. Watercourses in Pomurje and Velunja, Kožbanjšček, and Dragonja also dry up very often. Analysis results demonstrated that river drying has become more frequent in the past two decades. The driest month is August, followed by July and September.

The study evaluates the Rain on Grid (RoG) hydraulic model's sensitivity to Digital Elevation Model (DEM) resolution when simulating an extreme flood in Slovenia. The RoG model is validated against a high-resolution benchmark, showing strong agreement with a Kling-Gupta Efficiency of 0.913 and Pearson correlation of 0.964 for a 1 m DEM. Differences are observed in peak shapes and concentration times, attributed to rainfall propagation in RoG grids. DEM resolution significantly impacts performance, with the largest decrease between 1m and 5m resolutions. Coarser DEMs yielded higher depths, indicating slope decreases and terrain smoothing. The study concludes that high-resolution DEMs (<1m) are needed for adequate RoG performance, while commercially available coarser DEMs (30m) degraded accuracy and should be avoided using this method. Differences from semi-empirical concentration time models are also discussed, and an emphasis is given also on the impacts on water velocity and numerical stability.