There are many compelling arguments for using geothermal energy in Hungary. One of the most important is that the country could thereby exploit its abundant, relatively untapped network of geothermal reservoirs. These are considerably warmer and closer to the surface than in most of Europe. In the foreseeable future, Hungary’s geothermal resources can satisfy the conditions required for efficient energy production. The tremendous amount of energy stored in our geothermal reservoirs could satisfy much of the country’s long-term energy demand.Every geothermal project is designed to fulfill its project objectives by meeting time, budget, technical, and legal/regulatory provisions. Geothermal development is necessarily exposed to risks of varying degrees throughout its development, something which distinguishes geothermal from other kinds of renewable-energy projects. These risks most often concern the availability, amount, suitability, sustainability and use-potential of the geothermal resource, but may also include market, financing, commercial and macro-economic risks.
Groundwater quality evaluation is among the most critical aspects of water management concepts. As a result of overexploitation due to overpopulation, groundwater is severely deteriorating. Water Quality Index (WQI) is commonly used to appraise groundwater quality. In the present study, WQI model is developed to evaluate the groundwater quality in north Khartoum area. To classify water quality for diverse reasons, WQI uses multiple asset classes, sub-indices, and an accumulation function. Multivariate statistical analyses were applied to test the correlation between different variables to draw on the main variables and processes affecting the groundwater quality in the study area. Furthermore, correlation analysis (CA) and principal component analysis (PCA) served as guide for weights assignment in WQI calculations and interpretation. The innovative statistically guided WQI models (SWQI) proved to be superior in groundwater quality assessment. Although SWQI models is powerful and effective tool in groundwater assessment, however, conventional computation is lengthy, time consuming and is often observed with enormous errors during the calculation of sub-indices. In this study, artificial intelligence techniques are applied to cope with these limitations. Multilayer perceptron (MLP) and support vector regression (SVR) models were used for prediction of WQI. The dataset was divided into two groups (ratio 80:20) for training and validation respectively. The predicted models were compared with actual models using four statistical criteria, namely mean square error (MSE), root mean squared Error (RMSE), mean absolute error (MAE), and coefficient of determination (R2). The obtained results revealed the robustness of the artificial intelligence in prediction of WQI in north Khartoum area. The developed approaches in this study shown to be advantageous in groundwater quality assessment.
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.
In our work, a preliminary hydrogeological investigation was carried out to identify the thermal bath of Hajdúdorog’s hydrogeological setting and analyze the area which it is in. Literature review was performed to understand the geological, hydrogeological conditions as well as analyzing the production wells of the bath themselves. Based on the analysis a simple hydrodynamic modeling was performed to better understand the magnitude of the volume of water that can be extracted without disturbing the nearby Hajdúnánás Bath. Based on Our results, the Hajdúdorog Bath can produce more water from the aquifer to initiate infrastructural expansion for the future.
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