Aim of the study: The objective of the present study was to analyse the presence of metal elements in bottom sediments of water reservoirs in the basins of streams flowing from mountain ranges, containing metals, and to compare them with the composition of the tributary bottom material representing part of the parent rock of the basin, specifically Fe, Zn, As, Sr, Zr, Al and Ni. The subsequent step involves determining the transport of these elements within the streams and their subsequent accumulation within the reservoir. Material and methods: The study was conducted in two water reservoirs: Kučišdorf in the Pezinok cadastral area, and Harmónia in the Modra cadastral area. Both water works serve mainly for the recreation and sport fishing. The samples were taken in 2024, and analysed in 2024 and 2025. Samples were analysed using a handheld X-ray fluorescence spectrometer (XRF), model Vanta. The arithmetic mean was calculated from the five performed analyses, which were then used in the evaluation. The results were processed in MS Excel. Results and conclusions: The results indicate that the bottom material at the inflow and reservoir bottom sediments contain a wide variety of elements, including a wide range of metals. It is evident from the results that the concentrations of the monitored elements are principally supplied to the bottom sediments from the tributary bottom material, and that these elements are accumulated in the sediments.
Aim of the study This study addresses the growing concern of water pollution in rural areas, where limited monitoring can affect both human health and ecosystem stability. Contamination of freshwater resources has become an important environmental and public health issue, prompting the need for detailed local assessments. This study assesses pollution status and water quality in Baicë village, Kosovo, a rural area where limited monitoring can affect both human health and ecosystem stability. Material and methods Groundwater samples were analyzed for key physicochemical parameters and heavy metals, including Cr, Al, Cu, Fe, Mn, Ni, Pb, Zn, As, and Cd. The results revealed significantly elevated concentrations of lead at all sampling points (M1: 0.27 mg/L, M2: 0.25 mg/L, M3: 0.29 mg/L), exceeding recommended limits and indicating serious contamination. Elevated levels of other parameters, including COD and BOD5, further suggest anthropogenic impacts on water quality. Results and conclusions Toxic element levels, including Cr, Al, Cu, Fe, Mn, Ni, Pb, Zn, As, and Cd, were analyzed using Inductively Coupled Plasma-Optical Emission Spectrometry (ICP-OES), providing additional insights into contamination. Furthermore, geospatial analysis using GIS and Inverse Distance Weighting (IDW) interpolation generated contamination hotspot maps, revealing spatial variations and helping identify priority areas for targeted remediation efforts. However, due to the limited number of sampling locations and temporal coverage, the results should be considered a preliminary assessment and further monitoring is recommended to improve the understanding of groundwater contamination patterns in the study area.
Aim of the study The research problem of this study is to model and track the surface water temperature changes in the Euphrates River at Al-Hindiya Barrage, Iraq, by relying on in-situ measurements and Landsat 8/9 satellite (2018–2024) Material and methods This study employed GIS and statistical methods to process field observations and Landsat satellite thermal infrared images to determine average monthly surface water temperatures. The Landsat dataset had about 4.8% missing data points, while on-site measurements had approximately 1.2% missing values. Missing data were reconstructed using IBM SPSS Statistics (Version 26) through mean compensation, substituting missing values with the arithmetic mean of the same month across available years. This approach ensured a stable and reliable time series, enabling modeling of the relationship between on-site and satellite-measured temperatures via simple linear regression. Linear regression performance at Hindiya Barrage was assessed using the Nash–Sutcliffe efficiency coefficient. Results and conclusions Results show that in-situ water temperatures produced significant monthly temperature variation (actual water temperatures ranged from a minimum of 11.8°C to a maximum of 32.9°C), and satellite data recorded even wider temperatures ranging from a minimum of 12.0°C to a maximum of 40.8°C. A highly significant correlation (R² = 0.93) between datasets shows that Landsat-derived water temperature values. NSE reached 0.89 indicating excellent agreement between observed and estimated values. These findings validate Landsat for monitoring water temperature, supporting water resource management and ecosystem protection. Integrating remote sensing with traditional methods enhances assessment accuracy for environmental decision-making and adaptation. The low-cost predictive linear regression aids monitoring in data-scarce and arid areas.
Aim of the study: To generate a landslide susceptibility map using Hybrid Approach of FR Model and Geospatial Technology for the studied area. Material and methods: Application of FR Model and GIS Results and conclusions: According to the FR method, 11.5% areas are very highly susceptible to landslides, 23.2% represents highly susceptible area, and 26.2% represents moderately susceptible areas. Low susceptibility areas constitute 26.5%, and very low susceptibility areas, 12.6%. Susceptibility classes in the final map were derived from FR method, grouped into five risk levels and examined with the value of area under curve (AUC). When it came to zoning the study regions in relation to past landslides, the FR model produced an AUC of 73.4%. Therefore, using the assessment of the landslide susceptibility map, it has been demonstrated that the approaches employed produced findings that were satisfactory in their reliability.
Celem pracy było określenie stopnia rozproszenia zabudowy na wybranych obszarach wiejskich województwa małopolskiego w latach 2014 oraz 2024 z wykorzystaniem wskaźników autokorelacji przestrzennej (Morana I). Testowano hipotezę o większym skupieniu zabudowy na obszarach z wysokim pokryciem miejscowymi planami zagospodarowania przestrzennego (mpzp) w porównaniu do terenów rozwijanych głównie na podstawie decyzji o warunkach zabudowy. Badanie obejmowało analizę czterech gmin o różnym stopniu pokrycia miejscowymi planami zagospodarowania przestrzennego w latach 2014–2024, wykorzystując dane BDOT10k. Obliczono statystyki globalne i lokalne Morana I w środowisku QGIS dla wybranych obszarów. Analiza oparta była na siatce kwadratów 250x250m. We wszystkich gminach wartości globalnego wskaźnika Morana były dodatnie (0,36–0,49), wskazując na tendencję do skupienia zabudowy, z wyraźnym udziałem rozproszenia. Wartość wskaźnika wzrosła w każdej gminie ( od 3% do 9%) na przestrzeni 10 lat. Analiza lokalna wykazała stabilność głównych klastrów zwartej zabudowy (HH) oraz terenów niezabudowanych (LL). Uzyskane wyniki nie potwierdziły hipotezy – wzrost autokorelacji przestrzennej zaobserwowano we wszystkich badanych obszarach, ale jego intensywność nie była proporcjonalna do stopnia pokrycia miejscowymi planami zagospodarowania przestrzennego.
