22-27 September 2019
Trade Fairs and Congress Center (FYCMA)
Europe/Madrid timezone

Examination of the hydrologic cycle with long-term precipitation and groundwater level data

23 Sep 2019, 12:00
15m
Multiuse room 2 ()

Multiuse room 2

Oral Topic 2 - Groundwater and climate change Parallel

Speaker

Mr Csaba Ilyés (University of Miskolc MTA-ME Geoengineering Research Group)

Description

The impact of the ever-changing climate on Earth is already evident in the emergence of weather extremes and increased water demand from the agriculture. These changes and the human responses to it can greatly change many elements of the hydrological cycle. Weather extremes all appear in the amount and intensity of the fallen precipitation, while increased water demand in many areas has led to a permanent water level decrease in mainly shallow groundwater aquifers.
Examining the changes requires large amounts of measured data, both for rainfall and water levels. In our study, these two elements of the hydrological cycle were analyzed in the Carpathian Basin involving several sample areas.
Changes in the amount and time distribution of the fallen precipitation were investigated across the entire Carpathian Basin by analyzing more than 100-year-long data sets, while the impact of the increased water demand was analyzed for the largest continuous agricultural area at the Hungarian Great Plain.
The different hydrological time series were analyzed by various mathematical methods. Spectral analysis based on the Discrete Fourier transformation was used to study long-term precipitation and shallow groundwater time series, and several deterministic cycles were calculated. In both rainfall and groundwater data, we have identified 13 cycles that were found in each time series, just like the 5-year, 12-year, and 4.5-year long cycles. With the help of Wavelet analysis, we also examined the extent to which these cycles changed during the 20th century, and whether there was an increase in the stochastic effects.
On long-term shallow groundwater time series, a complex method of factor and cluster analysis were performed based on the linear modeling of each monitoring point’s seasonality, so data sets were generated from the often incomplete time series registered in different measurement intervals, which will later meet the conditions of the spectral analysis.
The research was carried out within the GINOP-2.3.2-15-2016-00031 "Innovative solutions for sustainable groundwater resource management" project of the Faculty of Earth Science and Engineering of the University of Miskolc in the framework of the Széchenyi 2020 Plan, funded by the European Union, co-financed by the European Structural and Investment Funds.

Primary authors

Mr Csaba Ilyés (University of Miskolc MTA-ME Geoengineering Research Group) Dr Endre Turai (University of Miskolc) Prof. Péter Szűcs (University of Miskolc)

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