Continuous monitoring of the health status of vineyards is essential for gaining a deeper understanding of plant physiological processes and for optimizing agricultural management practices.
Researchers from the HUN-REN ATK Institute for Soil Sciences studied the development of vegetation health indices at three research sites within a small catchment area in the Balaton Uplands. They paid particular attention to the temporal dynamics of the Normalized Difference Vegetation Index (NDVI), an indicator that provides information on vegetation density and health based on the ratio of near-infrared and red reflectance.
During the two-year study, field-based instrumental measurements and satellite remote sensing data collection were carried out simultaneously on two vineyards and a grassland site.
The aim of the research was to refine the values of satellite-based vegetation indices, which provide wide spatial and temporal coverage but low spatial resolution, by integrating data obtained from field measurements, using machine learning methods.
The results showed significant differences in vegetation indices between the study sites, primarily explained by variations in the chemical composition of the soils. The NDVI values derived from satellite and field measurements were strongly correlated. The machine learning models used in the study performed well even with basic input data. The researchers also demonstrated that the performance of each model improved significantly when data from the grassland area was included, illustrating that the method can be used to obtain more accurate values for the health status of grass covered inter-row managed vineyards.

Understanding the interactions within the soil–plant–water system is essential for effective water and nutrient management, maximizing crop yields, enhancing biodiversity, and evaluating environmental impacts.
Researchers from the HUN-REN ATK Institute for Soil Science studied how changing tillage practices to cover cropping affected soil moisture variation in a vineyard located in the Balaton Uplands. The study spanned three years and included two vineyard treatments. In the first treatment, tillage was used in the first year, followed by the introduction of cover crops in the second year, and continued cover cropping without further tillage in the third year, allowing cover crops to regrow naturally. The second treatment, serving as a control, involved permanent grass cover with no tillage. Alongside soil moisture monitoring, the researchers also conducted plant and soil physical and chemical analyses.
The results revealed distinct differences between the inter-row treatments. Soil moisture content was significantly higher at both 15 cm and 40 cm depths in the tillage to cover-cropped site compared to the grass-covered site. Plant traits showed a moderate correlation with soil properties such as total nitrogen, pH, and soil water content. Although continuous cover cropping in the third year led to reduced soil moisture content in the upper soil layers, it had a positive effect on plant development.

Researchers with the lead of the Institute for Soil Sciences, HUN-REN Centre for Agricultural Research developed a high-resolution national “soil hydrologic groups” map for Hungary by integrating data-driven clustering with expert rules.
Using the HU-SoilHydroGrids dataset (100 m resolution, six depth layers, eight hydraulic parameters) as well as soil chemical and taxonomic maps, they first applied k-means clustering to partition soils by hydraulic behavior. Since purely statistical clustering tends to underrepresent extreme or rare soil types, they refined clusters via expert rules considering soil genetic type, rooting depth, electrical conductivity and sodium exchange content.
The result is 68 distinct soil hydrologic groups, each characterized by van Genuchten parameters and saturated hydraulic conductivity. They validated the grouped map using independent observations from a drought and water scarcity monitoring system, evaluating metrics like R², RMSE, bias and concordance. While aggregation reduces some accuracy, especially near saturation, the grouped map remains practical for large-scale hydrological modelling and environmental planning.
This map enables consistent treatment of soils with similar hydraulic behavior across Hungary, thus supporting watershed modelling, land use planning, drought assessment, and other environmental applications.

This study by Ágnes Vári and colleagues explores the socio-ecological system of Lake Balaton, focusing on how different user groups (local residents, second-home owners, and tourists) perceive and value the ecosystem services provided by the lake. Based on a survey of 1,500 respondents, the research identifies social preferences regarding recreational activities, shore types, and future development projects.

Respondents attributed the highest importance to regulating services (e.g., water quality maintenance, climate regulation) and cultural services (e.g., aesthetic beauty, quiet relaxation). This aligns with the finding that the most frequent activities are nature-based and require minimal infrastructure, such as swimming, walking, and observing wildlife. In contrast, high-impact activities like yachting or motorized water sports ranked significantly lower in importance.

The study’s most critical takeaway is that value judgments are primarily driven by environmental awareness rather than socio-demographic factors like age or gender.

• A clear majority (58–61%) of respondents disapprove of further intensive infrastructure development, such as new hotel complexes and large marinas.

• There is a strong preference for natural or near-natural shoreline types (reed beds, undeveloped banks) over artificial, built-up environments.

• The most significant differences in opinion were found between local residents and tourists, highlighting how daily proximity and attachment to the lake shape perception.

The research highlights a fundamental conflict in sustainable management: the demand for mass recreation often clashes with conservation goals (e.g., Natura 2000 protection). The authors propose a framework based on spatial multifunctionality. This suggests that the shoreline should be managed through targeted spatial planning that balances protection and usage, ensuring that human activities do not compromise the natural processes—such as the filtering function of reed belts—that sustain the lake’s health.

As part of the Sustainable Development and Technologies Program, this work addresses the challenge of managing groundwater resources in areas where detailed geological information is scarce. Without sufficient data about underground rock formations and water flow patterns, it becomes difficult to make informed decisions about water resource planning and sustainability.

This study presents an innovative solution to this problem by utilizing geophysical measurements from wells to understand and predict groundwater behavior. The research applies advanced analytical methods, including the Csókás method—developed by Professor János Csókás, former head of the Geophysical Department at the University of Miskolc—along with modern machine learning techniques to create reliable groundwater flow models even when traditional data is limited.

The results demonstrate that this approach can successfully map underground water systems and support sustainable water management decisions in regions with complex geology and limited available information.

A new research article published in highly ranked D1 journal “Geoscience Frontiers” demonstrates how advanced machine learning and geophysical techniques can revolutionize our understanding of groundwater systems in arid environments. The study, titled “Aquifer characterization and salinization origin using unsupervised machine learning and 3D gravity inversion modeling, Siwa Oasis, Egypt,” was conducted by Dr. Mohamed Hamdy Eid under the supervision of Prof. Dr. Peter Szucs and Dr. Attila Kovacs from the Institute of Water Resources and Environmental Management at the University of Miskolc.
Siwa Oasis, located in Egypt’s northwestern Western Desert, faces critical water management challenges due to its arid climate and complete dependence on groundwater resources. The oasis is home to approximately 23,000 people and extensive agricultural activities, yet groundwater salinization poses a significant threat to sustainability. The research addresses this challenge through an innovative integrated approach that combines unsupervised machine learning techniques with advanced gravity data analysis.
A critical finding of the research is the spatial relationship between groundwater salinity and structural complexity. The southern part of Siwa Oasis, characterized by reduced structural complexity, exhibits lower groundwater salinity and has been identified as the optimal area for fresh groundwater extraction. Conversely, central and northeastern regions show higher salinity zones that spatially correlate with gravity-derived structural systems, suggesting that fracture networks may facilitate leakage from hypersaline surface lakes into underlying aquifer systems.
This integrated approach represents a significant methodological advance for sustainable groundwater management in structurally complex arid environments. By combining the detailed lithological information from well logs with the spatial coverage of gravity surveys, the research provides a comprehensive three-dimensional understanding of aquifer geometry and the structural controls on groundwater flow and quality. The findings have direct implications for water resource planning and management strategies in Siwa Oasis and similar arid regions worldwide.

Szabó, Norbert Péter

A hyperparameter estimation-based inversion approach for evaluating shallow unsaturated formations is presented. Natural gamma ray intensity, bulk density, neutron porosity, and electrical resistivity borehole logs measured by direct-push probes are jointly inverted for estimating clay and sand volume, air and water content. The inversion algorithm is enhanced through the preliminary application of factor analysis. The first extracted factor exhibits a strong correlation with water content across various sites in Hungary. A linear relationship between the first factor and water content is assumed and integrated into the forward modeling process. Instead of estimating the water content separately at discrete borehole depths, a linear regression model is used, where the regression coefficients are determined by inversion to predict the depth variation of water content along the entire logging interval. These site-specific coefficients are treated as hyperparameters and predicted in a two-level embedded inversion algorithm. In the outer loop, hyperparameters are optimized with a differential genetic algorithm where volumetric parameters are fixed. In the inner loop, the volumetric quantities are calculated depth-by-depth by a quick linearized inversion. The estimation error of hyperparameters is calculated from the individuals of the last generation of the evolutionary search, while those for the volumetric quantities are derived using the data covariance matrix. Due to an increased data-to-unknowns ratio, the estimation accuracy is higher than local inversion methods. The hyperparameter inversion of direct-push logs sets new perspectives in solving environmental and groundwater problems by giving highly accurate and reliable input parameters for an improved characterization of unsaturated media.

Musaab A. A. Mohammed, Norbert P. Szabó, Joseph O. Alao and Péter Szűcs

In the framework of the Sustainable Development and Technologies National Program of the Hungarian Academy of Sciences (FFT NP FTA), our research focuses on the sustainable management of groundwater resources in arid and semi-arid environments. Sudan, where groundwater is the most dependable source of freshwater, faces severe challenges due to limited monitoring infrastructure, high dependence on aquifers, and the growing impacts of climate variability and human demand.

To address these challenges, we combined satellite-based geophysical observations from the GRACE and GRACE-FO missions with land surface data from the Global Land Data Assimilation System (GLDAS). This work demonstrates how the integration of geophysical satellite data and modern computational tools can provide new solutions for water resource management in data-scarce regions, supporting the overall goals of FFT NP FTA to promote sustainable development and technological innovation.

In the summer of 2025, a study was published in the Atmospheric Chemistry and Physics (D1) journal, aimed at comparing and evaluating the description of ozone dry deposition, as well as the individual component processes, in atmospheric chemistry models. The investigation involved 37 researchers from 24 institutions. The findings highlight the challenges in accurately describing the effects of moisture stress on the stomatal sink of ozone during dry periods, which are induced by ecosystem-specific plant–resource interactions. The methodology of the article is related to the tasks undertaken by the Photoacoustic Research Group at the University of Szeged within the FF&T program.

Click here  to the whole study: Atmospheric Chemistry and Physics

Slovakia is rich in balneological traditions, where numerous mineral springs have been historically used for therapeutic purposes. The Sobranecké Spa (“Salus per Aquam”) holds a remarkable history dating back to 1336 and is recognized as a Slovakian heritage site for its cultural and historical significance. The healing properties of its mineral-rich waters were first documented in the chronicle of Count Sztáray, where they were described as “Salt healing wells”. Today, this once-prosperous health retreat stands in a state of disrepair, serving as a reminder of its historical significance and the remarkable healing properties of its mineral waters. Recently, renewed interest from the Košice self-governing region has prompted efforts to restore the spa’s activity. This research is designed to assess the physiochemical and microbial characteristics and potential health risks associated with using this water for dermal therapeutic purposes. The findings from this study, as first of its type, serve as a scientific foundation for the spa’s rehabilitation, ensuring that its historical legacy is preserved while aligning with modern health and safety standards for medicinal water use.

Forward to the whole article: Environmental Challenges

Photos: Exterior and interior of the Main Spring in Sobranecké Spa