Due to the frequent climatic changes occurring worldwide, which are related to extreme meteorological parameters as well as human activities, it is obvious that these influence the flow regimes of rivers. River flow is the most important factor determining the hydrological regime of any river. This has a substantial influence on the water resources and the environment surrounding the river. Hydrotechnical structures are also dimensioned on the basis of the flow as the primary input parameter. The flow conditions have different properties and correlations with the material of the river bed. In this paper, possible dependencies and phenomena are investigated using real case studies on two rivers in Croatia - examples of river courses in alluvium and karst areas - with regard to homogeneity and isotropy analyses. For this purpose, rescaled adjusted partial sums and innovative polygon trend analysis methods will be applied on the form of a combination of methods at the same watercourses. It has been shown that the analysed time series of the flows do not exhibit homogeneity and isotropy. In addition, fluctuations and irregularities were detected in the same time series. This is key information for determining the reliability of the flow forecast.

In this research, the SWAT+ model was employed to elucidate hydrological dynamics within the Beas Basin. The primary objectives encompassed the calibration of the SWAT model for accurate water balance quantification, annual simulation of salient hydrological components, and a decadal analysis of trends in fluvial discharge and sediment transport. The methodology encompasses simulating hydrological data with the SWAT+ model, followed by calibration and validation using flow data from Larji and Mahadev hydroelectric plants. The model’s efficacy in depicting streamflow and other hydrological components is corroborated by statistical measures such as the Nash–Sutcliffe efficiency and PBIAS. The water balance analysis delivers insights into the basin’s hydrological characteristics, including surface flow, water yield, and evapotranspiration. The temporal analysis exposes intricate seasonal and interannual variability in flow and sediment discharge, while spatial distribution highlights heterogeneity across the basin. These findings have practical implications for water resource management, including optimizing water allocation, hydroelectric power generation, irrigation, and environmental concerns. Limitations, such as data quality and model simplifications, are acknowledged, and future data collection and observations are recommended for improved model performance. In essence, these researches enhance understanding of the Beas Basin’s hydrology, setting a course for future investigations to integrate more data sources, refine model parameters, and consider climate and land-use changes for a richer comprehension of the basin’s hydrological dynamics.

Concerning the media’s properties, there is always a possibility of changing groundwater flow conditions surrounding hydroelectric power plants. Causes for such events could be natural or anthropogenic, which is, in many cases, not so obvious to determine. In addition, determining a period when changes in the groundwater flow occur is a complex task. All of the above mentioned are of crucial importance due to the operational work of hydropower plants, i.e., the optimization of the inflow and outflow of the water in the turbine, regardless of the hydropower plant type. All types listed require a particular approach for solving such issues. Rescaled Adjusted Partial Sums (RAPS) is an appropriate time-series analysis method. In this specific case, observed fluctuations in the time series of the groundwater levels could lead to conclusions about possible irregularities in the shallow as well as the deep zones of the underground water. The concept was shown in this paper in the example of the hydroelectric power plant Mostar dam in Bosnia and Herzegovina. It should be noted that the defined methodology was a novel procedure for analyzing and determining the pathways of the flow of groundwater in the surrounding hydropower plant dams. In other words, such analysis could be conducted without the need for complex and expensive drilling and geophysical surveys, tracing, and all other methods.

: This paper presents a research conducted as part of development of the graduation thesis entitled: "Hydraulic numerical analysis of groundwater in the left hinterland of the Mostar hydroelectric power plant dam", which was developed and successfully defended at the Faculty of Civil Engineering, University of Mostar in 2020. The Mostar hydroelectric power plant, in tandem with the Salakovac HPP, levels the flows in the downstream course of the Neretva River. In the area around the embankment and the diaphragm wall, there are indications of filtration deformations of soil, and development of dominant directions of groundwater flows. The paper examines the area of the left hinterland of the Mostar hydroelectric power plant dam in the MAGNET 4 WATER program, and compares the obtained results with the existing verified results from the DHI WASY FEFLOW program as well as the field results. It was concluded that the spatial model is suitable for further research and analyses, e.g. for monitoring groundwater flows in the area, and for the analysis of risks of contaminant transport underground the left hinterland of HPP Mostar.

This paper gives an overview of the research conducted as part of the graduation thesis titled: "The hydraulic study of groundwater flows in the area of the lower PSPP Vrilo balancing reservoir", which was developed and successfully defended at the Faculty of Civil Engineering University of Mostar in 2018. The task was to develop a spatial model of steady groundwater flows in the area of the designed lower balancing reservoir of the Vrilo pumpedstorage power plant, based on field investigation data and data from the PSPP Vrilo preliminary design.

The object of this research is to compare three of the most popular conventional analytical models used for estimation of electrical energy production of photovoltaic panels. From this analysis a single model will be selected with the best characteristics for implementation of modifications and corrections in order to get better energy production prediction results. Monthly and annual production results and errors will be the main criteria for the selection of a single model. Single prediction results of the selected model should be as accurate as possible in the smallest time periods, which are in this case monthly energy prediction results. This should guarantee that annual results are also rather accurate. Streszczenie. W artykule porownano trzy modele analityczne umozliwiające analize energii elektrycznej wytwarzanej przez panele fotowoltaiczne. Analizuje sie miesieczną i roczną produkcje energii na podstawie wybranych okresow czasowych. (Porownanie metod przewidywania produkcji enegii przez panele fotowoltaiczne)