Tamás Mester

This study examines the spatiotemporal variability in groundwater quality at five monitoring locations in Dehradun, Uttarakhand, India, from 2021 to 2025, based on 40 site-period observations covering 33 physicochemical, ionic, trace metal and pesticide parameters. Most parameters complied with BIS IS:10500 (2012) standards, with total dissolved solids and total hardness well within limits. Sulphate peaked at 260.5 mg/L at a landfill site in 2023, and iron reached 13.2 mg/L at an industrial site, while arsenic, mercury, lead, cadmium and four organochlorine pesticides stayed below detection. Trend analysis showed significant declines in TDS, sulphate and sodium and a significant rise in pH, indicating improving water quality since 2021, although a sensitivity check restricted to 2022–2024 showed the pH and sulphate trends were driven mainly by recovery from the 2021 baseline rather than a continuing multi-year trend. A major-ion Water Quality Index classified groundwater as excellent to good at all sites, while a Heavy Metal Pollution Index, driven mainly by chromium in 2021 and nickel in post-monsoon 2022 rather than by iron, exceeded the critical value of 100 in 11 of 40 site-period observations. Piper trilinear analysis identified a predominantly Ca-HCO₃ hydrochemical facies at the individual-sample level, with a minority of samples showing mixed or sulphate-leaning compositions. A human health risk assessment based on copper, zinc, nickel and chromium showed hazard indices above the safety threshold at all sites in 2021, largely due to a conservative assumption that all measured chromium was present as the more toxic Cr(VI) form, with substantially lower hazard-index values from 2023 onward under the primary zero-substitution convention for below-detection-limit metals. A sensitivity check substituting half of the laboratory’s documented detection limits for non-detect readings in these metals placed all 40 site-periods in the critical HPI band and raised the child hazard index above 1 in every 2022–2025 round outside post-monsoon 2022, so the post-2021 improvement is assumption-dependent. Conventional irrigation indices indicated low sodium and salinity hazards, although the very low electrical conductivity implies potential infiltration constraints under FAO EC-SAR guidance.

Floodplain oxbow lakes and natural levees preserve sedimentary archives that can provide information on long-term changes in depositional environments. This study investigates three oxbow lake–natural levee pairs of different ages along the Upper Tisza River using 258 sediment records. Grain size composition, pH, electrical conductivity, CaCO₃-equivalent values, and organic carbon were characterized. Spearman correlation analysis was used to examine relationships among the measured properties, while principal component analysis (PCA) was performed using pH, electrical conductivity, organic carbon, and isometric log-ratio-transformed grain-size data. The profiles showed pronounced vertical and between-site heterogeneity, indicating that geomorphological position alone does not determine sediment properties. PCA identified four major sedimentological and geochemical gradients, whereas cluster analysis distinguished four broad sediment groups with distinct sedimentological and geochemical characteristics. These multivariate statistical analyses revealed relative vertical zonation and sedimentological and geochemical changes associated with oxbow-lake infilling and natural-levee development. Long-term mean sediment accumulation rates were estimated separately from the multivariate analyses using sediment thickness, documented channel-cutoff ages, and, where applicable, stratigraphic correlations. Time-averaged post-cutoff oxbow-lake sediment accumulation rates were approximately 10.2 cm yr⁻¹ for GYM1, 4.56 cm yr⁻¹ for GYM2, and ≤4.62 cm yr⁻¹ for GYM3. For the natural levees, no accumulation rate was estimated for GYF1 because of the absence of an independent chronological marker, whereas tentative correlation of buried paleosol horizons in GYF2 and GYF3 with dated paleosols on the Bereg Plain suggests conditional long-term mean accretion rates of approximately 0.042–0.090 cm yr⁻¹ for GYF2 and 0.032–0.069 cm yr⁻¹ for GYF3, respectively. Integrating vertical sedimentological and geochemical records with multivariate statistical analyses and independent chronological and stratigraphic constraints therefore provides a framework for reconstructing relative depositional succession and estimating long-term sediment accumulation during floodplain evolution.

Shallow groundwater systems of rural municipalities are highly vulnerable to long-term contamination from former on-site sanitation systems, while the hydrochemical response of the aquifer after sewerage network development may be delayed by several factors. In the present study, a total of 147 shallow groundwater samples collected during the summer sampling campaigns of 2018, 2019, 2023, and 2024 were analyzed for general water-quality parameters including pH, EC, NH₄⁺, NO₂⁻, NO₃⁻, PO₄⁻, Cl⁻, SO₄²⁻, microelements, and potentially toxic elements, including As, Pb, Cd, Ni, Cu, Zn, Fe, and Mn. The dataset was evaluated using descriptive statistics, Piper, Wilcox, and Gibbs diagrams, hierarchical cluster analysis, principal component analysis, and GIS-based spatial interpolation. The results indicate that, more than ten years after sewerage network development (2014), shallow groundwater in the study area still shows considerable contamination, primarily characterized by elevated mean concentrations of ammonium (0.836 mg/L), nitrate (177.43 mg/L), and chloride (313.26 mg/L), accompanied by high electrical conductivity (3115 µS/cm) and sodium enrichment (378.12 mg/L). Spatial and boxplot analyses of SAR further indicated increasing sodium-related heterogeneity after 2018, with higher local SAR values in 2023–2024. Hydrochemical diagrams revealed a shift towards Ca-Cl type to Na–Cl types, while multivariate analyses confirmed that salinity enrichment, nitrate contamination, water–rock interaction and redox-sensitive trace element mobilization act as overlapping but partly separable controls. The nitrate–chloride source plot indicated mixed contamination origins, dominated by residual sewage influence and manure-related inputs, with diffuse agricultural nitrogen leaching. Arsenic was used as a supporting indicator of mixing with wastewater; however, As was no longer detectable in most of the investigated wells, suggesting a marked reduction in the former wastewater leakage. These results support the slow attenuation of contamination in the shallow groundwater system affected by former wastewater infiltration and highlight the need for continuous monitoring.

Freshwater shallow lakes are vulnerable to global warming, putting entire aquatic ecosystems at risk, but evidence from managed reservoirs remains limited despite the existence of long-term empirical data. Using data from 29 stations on Lake Tisza covering an 18-year period (2007–2024), this study quantifies warming rates, thermal stress patterns and trends in water quality in lacustrine, transitional and riverine zones. Lake areas warmed at a rate of 0.90 °C/decade (p < 0.001), faster than the river/transition areas and even than global averages in shallow lakes. Temperature-critical years now affect 90.4% of lake stations, compared with 59.6% in 2007–2012. A strong negative correlation between temperature and dissolved oxygen was observed along all systems (Spearman’s p; river: −0.83, transition: −0.65, lake: −0.53), indicating thermal-driven deoxygenation risk. At the same time, a water quality index (conductivity, pH, BOD₅, total nitrogen and phosphorus, total coliforms) showed an improvement (lake WQI: 63.7 to 74.3). Principal component analysis explained 85% of its variance, showing spatial gradients of eutrophication and fecal contamination, with lacustrine homogenization suggesting management interventions. Lake Tisza is warming faster than global shallow lake averages, with critical implications for the ecosystem’s function; nonetheless, the coexistence of thermal deterioration with improvements in its WQI reveals the effectiveness of the intermittent discharge system and the need for climate-adapted monitoring frameworks that incorporate thermal vulnerability into water quality assessment for regulated shallow lakes under climate change pressure.

The study examined climate concern (CC) and pro-environmental behaviour (PEB) regarding climate change. In our research, we chose the second largest city in Hungary, Debrecen. We conducted a questionnaire survey among residents in 2020 (N = 200). The closeness, strength and intensity of the relationship between the predictors, Total Climate Concern Index (TCCI) and PEB Index (PEBI), were examined by correlational analyses. Regression analysis investigated selected variables' relative impacts on and relationships to TCCI and PEBI. We revealed that the TCCI of inhabitants is very high, but PEBI is much lower. In correlational analyses, TCCI and PEBI were each separately found to correlate positively and significantly with AI (Attitude Index, which comprises risk perception and confident willingness to change lifestyle). ...

This study aims to evaluate the obstacles and possibilities for promoting community-based ecotourism in Bale Mountains National Park (BMNP) Ethiopia and to summarize and present the lessons that European countries can learn from the empirical ...

In the present study, the changes in the groundwater quality in a Hungarian settlement, Báránd, were examined, nine years after the construction of a sewerage network. The sewerage network in the study area was completed in 2014, with a household connection rate exceeding 97% in 2023. In the summer of 2023, water samples were taken from 37 dug groundwater wells. Changes in the water quality were assessed using three water quality indicators (the Water Quality Index (WQI), Contamination degree (Cd), and Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI)) and geographic information (GIS), data visualization systems, and artificial intelligence (AI). During the evaluation of the quality of the groundwater, eight water chemical parameters were used (pH, EC, NH₄⁺, NO₂⁻, NO₃⁻, PO₄³⁻, COD, Na⁺). Based on interpolated maps and water quality indices, it was established that while an increasing portion of the area exhibits adequate or good water quality compared to the pre-sewerage period, a deterioration has occurred relative to recent years. Even nine years after the sewerage network construction, elevated concentrations of inorganic nitrogen forms and organic matter persist, indicating the continued presence of accumulated pollutants, as confirmed by all three water quality indicators to varying degrees and spatial patterns. The interactive data visualization and cloud-based sharing of the data of the water quality geodatabase were made freely available with the help of Tableau Public. A Feed-Forward Neural Network (FFNN) was developed to predict the groundwater quality, estimating the water quality statuses of three water quality indicators based on water chemistry parameters. The results showed that the applied training algorithms and activation functions proved to be the most effective in the case of different network structures. The most accurate prediction of the WQI and CCME WQI indicators was provided by the Bayesian control algorithm (trainbr), which achieved the lowest mean-squared error (RMSE_WQI = 0.1205, RMSE_{CCME WQI} = 0.1305) and the highest determination coefficient (R²_WQI = 0.9916, R²_{CCME WQI} = 0.9838). For the Cd index, the accuracy of the model was lower (RMSE = 0.1621, R² = 0.9714), suggesting that this indicator is more difficult to predict. With regard to our study, it should be emphasized that data visualization is a particularly practical tool for the post-processing of spatial monitoring data, as it is suitable for displaying information in an intuitive, visual form, for discovering spatial patterns and relationships, and for performing real-time analyses. AI is expected to further increase visualization efficiency in the future, enabling the rapid processing of large amounts of data and spatial databases, as well as the identification of complex patterns.

Increasing anthropogenic disturbance in urban areas and the expansion of built-up zones into surrounding rural landscapes represent one of the most significant spatial and ecological challenges of recent decades. Urban expansion influences not only land use patterns but also the ecological integrity and naturalness of the landscape. In the present study, anthropogenic landscape change trends and changes in land cover categories were investigated within the current administrative boundaries of Nyíregyháza, a county seat located in northeastern Hungary. Using data from the CORINE Land Cover program (1990, 2000, 2012, 2018) and historical military surveys (1819–1869), landscape development trends within the municipality were examined over the past one and a half centuries. Particular attention was focused on examining changes in the extent of built-up areas, which are among the most concerning from a landscape ecological perspective. By comparing the results with data from other Hungarian cities (Debrecen and Szeged), a significant increase—nearly 20%—in built-up areas was identified. The proportion of built-up areas in relation to the total municipal administrative area increased in all the periods studied, even in those where the population was decreasing. This indicates that even in municipalities experiencing demographic decline, internal population redistribution may lead to the spatial growth of certain neighborhoods, which are the primary contributors to the expansion of built-up urban areas. Finally, based on CORINE Land Cover data, the ecological conditions of Nyíregyháza were assessed, and a hemeroby map of the municipality was created, reflecting landscape changes that occurred between 1990 and 2018. It was found that over a 28-year period, the total area of the most ecologically problematic meta- and polyhemerobic categories increased by 6%, in parallel with the growth of built-up areas.

Angling tourism is becoming increasingly important at Central Europe’s largest lowland reservoir, Lake Tisza. The lake, created in the 1970s, covers 127 km² and has been increasingly used for recreational and nature conservation purposes recently. This study seeks to identify anglers’ site selection preferences at Lake Tisza, considering hydrological and ecological aspects, in support of sustainable site management. In order to achieve this, an in-person questionnaire survey was carried out covering the whole area during springtime 2024. During the survey period, a total of 224 anglers provided answers about their preferred location and recreational characteristics. Data processing was carried out using SPSS 26 and ESRI ArcGIS version 10.4.1. Based on the created catchment area map, it was found that a significant proportion (74%) of anglers arrive from within a 50 km radius, but the lake also has appeal outside the country. A total of 53.1% of respondents visit the lake several times per month, typically for fishing purposes. In addition, cycling, walking and picnicking are popular recreational activities among anglers. The respondents considering different landscapes (pictures showed by the interviewers) for angling prefer shaded areas with vegetation and a narrow view of the wide expanse of water (62%). The results of the open-ended questions indicate that site selection is primarily based on the existence of a shadow (49.5%), and suitability for fishing is only the second aspect (40.6%). Our study also highlighted the international trend that anglers are more interested in leisure activities in a green environment. In addition, the results have practical significance for more successful recreation planning and sustainable site management.