The aim of our research was to better understand the spectral characteristics of precipitation variability, because through infiltration, this is the most important source of groundwater recharge. To better understand the periodicity of the rainfalls, we used monthly and annual rainfall data. We examined precipitation time records over a 110-year period from two different cities in the Carpathian Basin, obtained from the Hungarian Meteorological Service. With discrete Fourier-transformation (DFT) and wavelet time series analysis, we defined local cycles and developed a forecast for the Debrecen area.Using DFT, we calculated the time-period distributions (spectra) of monthly and annual rainfall data. Spectra from the annual rainfall data showed 16 dominant periods in Debrecen and 17 in Pécs. At the two stations, the most dominant cycles were 3.6 and 5 years, respectively; there were several other cycles locally present in the data sets. From the monthly data sets, several other periodic components were cal...

In recent years water-related issues are increasing globally, some researchers even argue that the global hydrological cycle is accelerating, while the number of meteorological extremities is growing. With the help of large number of available measured data, these changes can be examined with advanced mathematical methods. In the outlined research we were able to collect long precipitation datasets from two different climatical regions, one sample area being Ecuador, the other one being Kenya. Using the methodology of spectral analysis based on the discrete Fourier-transformation, several deterministic components were calculated locally in the otherwise stochastic time series, while by the comparison of the results, also with previous calculations from Hungary, several global precipitation cycles were defined in the time interval between 1980 and 2019. The results of these calculations, the described local, regional, and global precipitation cycles can be a helpful tool for groundwater management, as precipitation is the major resource of groundwater recharge, as well as with the help of these deterministic cycles, precipitation forecasts can be delivered for the areas.

This paper introduces a methodology for forecasting spring hydrographs based on projections from regional climate models. The primary study objective was to evaluate how climate change may affect spring discharge. A statistical–analytical modeling approach was developed and applied to the Jósva spring catchment in the Aggtelek Karst region of Hungary. Historical data served to establish a regression relationship between rainfall and peak discharge. This approach is particularly useful for predicting discharge in cases where only historical rainfall data are available for calibration. Baseflow recession was analyzed using a two-component exponential model, with hydrograph decompositionand parameter optimization performed on the master recession curve. Future discharge time series were generated using rainfall data from two selected regional climate model scenarios. Both scenarios suggest a decline in baseflow discharge during different periods of the 21st century. The findings indicate that climate change is likely to intensify hydrological extremes in the coming decades, irrespective of whether moderate or high CO₂ emission scenarios unfold.

A number of climatic cycles and teleconnections are known on the Earth. By definition, the cycles can have a periodic effect on the global climate, while teleconnections can influence the weather at large distances. At the same time, it is overwhelmingly assumed that the hydrological cycle is permanently intensifying all over the world. In this study, we determine and quantify some connections among these climatic cycles and precipitation data from across Hungary. By using cross-correlation and cross-spectral analysis, the connections of the climatic patterns and oscillations with the precipitation of different Hungarian areas have been defined. We used the 1950–2010 timeframe in order to be able to detect effects of several climatic patterns, such as the El Niño-Southern Oscillation (ENSO), the Arctic Oscillation (AO), the North Atlantic Oscillation (NAO), the Pacific/North American teleconnection pattern (PNA) and the Atlantic Multidecadal Oscillation (AMO) on the rainfall events of the Carpathian Basin. Data from four different precipitation measurement sites and oscillation indexes from several databases were used. The results help to understand the patterns and regularities of the precipitation, which is the major source of natural groundwater recharge, and a handy tool for future groundwater management measures. Because of the defined connections, any changes in these teleconnections will probably influence the future utilization of the Hungarian groundwater resources.

From a water management point of view, it is particularly important to be able to examine the temporality of the precipitation that replenishes the shallow or even deeper groundwater layers. In our study, we use a method that allows us to analyze the evolution of both the precipitation and groundwater levels together. With cross-correlation and cross-spectral analyses, we can quantify the relationship between the two hydrological parameters for a given sample area, and the periods found in the relationship can also be detected. During our calculations, we were able to determine such delay times for a sample area in Debrecen using monthly and daily data series, so an 8-10 month and a shorter 3-4 day linear relationship between precipitation and groundwater was detected. Based on our results, several periodic components can also be found in this elation.