Soil salinization is one of the main threats to soils worldwide, which has serious impacts on soil functions. Our objective was to map and assess salt-affectedness on arable land (0.85 km²) in Hungary, with high spatial resolution, using a combination of ensemble machine learning and multivariate geostatistics on three salt-affected soil indicators (i.e., alkalinity, electrical conductivity, and sodium adsorption ratio (n = 85 soil samples)). Ensemble modelling with five base learners (i.e., random forest, extreme gradient boosting, support vector machine, neural network, and generalized linear model) was carried out and the results showed that ensemble modelling outperformed the base learners for alkalinity and sodium adsorption ratio with R² values of 0.43 and 0.96, respectively, while only the random forest prediction was acceptable for electrical conductivity. Multivariate geostatistics was conducted on the stochastic residuals derived from machine learning modelling, as we could reasonably assume that there is spatial interdependence between the selected salt-affected soil indicators. We used 10-fold cross-validation to check the performance of the spatial predictions and uncertainty quantifications, which provided acceptable results for each selected salt-affected soil indicator (for pH value, electrical conductivity, and sodium adsorption ratio, the root mean square error values were 0.11, 0.86, and 0.22, respectively). Our results showed that the methodology applied in this study is efficient in mapping and assessing salt-affectedness on arable lands with high spatial resolution. A probability map for sodium adsorption ratio represents sodic soils exceeding a threshold value of 13, where they are more likely to have soil structure deterioration and water infiltration problems. This map can help the land user to select the appropriate agrotechnical operation for improving soil quality and yield.

The Nitrates Directive aims (a) to protect water quality across Europe from nitrates originating from agricultural sources that pollute ground and surface water, and (b) to promote good farming practices. One of the most controversial measures of the directive is the winter prohibition period of fertilization, which has been extended by a month in two steps in recent years. According to the regulation, it is forbidden to apply nitrogen fertilization in Hungary between 31st October and 15th February, even though the winter climate is gradually becoming milder. Using the fertilization data of nearly half a million parcels of land in the Hungarian Nitrate Database, a crop model-based spatial analysis was carried out. Our aim was to test if a shift in the prohibition period starting date from 31st October to 30th November caused any differences in the nitrate amount leached at a 90 cm depth. Detailed nitrate inputs and soil and weather databases were coupled with the 4M crop model. The yield, plant nitrogen uptake, and nitrate leaching under five major crops were simulated, covering a considerable portion of arable land. Shifting the prohibition period starting date did not result in significant changes in the nitrate leaching. Further runs of the 4M model with different weather scenarios are needed to decide whether the modification of the prohibition period significantly affects the amount of nitrate leached.

Since soil spectroscopy is considered to be a fast, simple, accurate and non-destructive analytical method, its application can be integrated with wet analysis as an alternative. Therefore, development of national-level soil spectral libraries containing information about all soil types represented in a country is continuously increasing to serve as a basis for calibrated predictive models capable of assessing physical and chemical parameters of soils at multiple spatial scales. In this article, we present a database containing laboratory and visible-near infrared spectral data of legacy soil samples from the Hungarian Soil Degradation Observation System (HSDOS). The published data set includes the following parameters measured in 5,490 soil samples: pH_KCl, soil organic matter (SOM), calcium carbonate (CaCO₃), total salt content (TSC), total nitrogen (TN), soluble phosphorus (P₂O₅-AL), soluble potassium (K₂O-AL), plasticity index according to Hungarian standard (PLI), soil profile depth and reflectance data between 350 and 2,500 nm wavelength. The presented database can be a complement for further soil related research on continental, national or regional scales to support sustainable soil management.

This review summarizes the role of soil in climate change mitigation and highlights the potential of agricultural practices to support this effort. It provides an overview of methods that enhance soil carbon sequestration and reduce carbon dioxide emissions from soils. After presenting a brief global overview, we focus on how the organic carbon stocks of Hungarian agricultural areas have changed over the past decades, underscoring the importance of climate-smart agricultural practices. We examine how these practices—such as cover crops, conservation tillage, fertilization, crop rotation, regenerative agriculture, and agroforestry—affect soil carbon stocks. While the review draws on global research, its primary focus is on practices applicable in Hungary. The effectiveness and feasibility of these climate-smart agricultural practices depend significantly on local climate, geographical location, and soil conditions. Therefore, we thoroughly analyze the applicability and limitations of each practice within the Hungarian context. In addition, we explore temporal trends to assess how the adoption of certain climate-smart practices has evolved over the past one to two decades. Lastly, we discuss the challenges of implementing the presented practices from economic, policy, regulatory, and human perspectives.

A kovával átitatott, alig mállott riolittufát feltáró fúrásban élénk vízmozgás volt megfigyelhető a fizikai aprózódás során felnyílt kőzetrepedéseknek köszönhetően, a mérések alapján számolt hidraulikus vezetőképessége a vályog–homokos vályog fizikai talajféleségű szintekéhez hasonló. A megjelenése alapján „vulkáni homok”-ként aposztrofált, mállott riolittufa víz-vezető képessége az előzetesen vártnál kisebb volt, nagyságrendekkel maradt el a „tényleges” homok vezetőképességétől, megjelenése jelentősen lelassította a szel-vényekben tapasztalt vízmozgást; számolt hidraulikus vezetőképessége nagyság-rendileg az agyagos vályogéhoz áll közel. A tapasztalt jelenség oka egyrészt az, hogy a mállás során a kőzetrepedések eltömődtek, eltűntek, másrészt pedig az, hogy a mállott agyagos rész a durvább szemcséjű „mállási maradék” pórusterébe üleped-ve a nedvességmozgás számára rendelkezésre álló pórusteret jelentősen lecsökken-tette. Az eredmények azt jelzik, hogy a szőlőterületek termőhelyi adottságait meghatá-rozó tényezők értékelésénél nemcsak a felszínközelben található kőzet típusát, de annak mállottsági fokát is figyelembe kell venni. Munkánkat a Tokaj Kereskedőház Zrt. támogatta. The Tokaj Wine Region is situated in northwestern Hungary and has been known as a significant production area of the sweet botritized dessert wine known as “Aszú” since the Middle Ages. Its reputation can be attributed to the geological and pedological features of the area, the special microclimate and the unique mould infection, combined with long years of experience. In 2013 the Hungarian Government set up a programme of sustainable quality wine production in the Tokaj region, coordinated by the Tokaj Kereskedőház Ltd, the biggest wine producer. To achieve this target it was indispensable to assess the potential of the vineyard soil. The viticultural characterization of the land was carried out during two main surveying phases (2013–2015). The primary objective of the present work was to contribute to terroir zoning by examining how the weathering of rhyolite tuff, the most common parent material in this region, influences soil water management, with special emphasis on saturated hydraulic conductivity, one of the characteristic factors. The conductivity values were calculated at four locations, based on borehole infiltration tests, which proved to be a feasible in-situ measuring technique. The textural composition (Figure 1) of the excavated soil layers and the calculated conductivity values were used to determine the conductivity of rhyolite tuff detritus. Rhyolite tuff was excavated from three boreholes (Nos. 3, 4, 6), while borehole No. 5 consisted of only rock debris (Figure 3). During the measurements the boreholes were filled up with water several times, the time dependence of the water level changes was recorded, and the standard Hungarian protocol (MÉM NAK, Table 1) was used to calculate the hydraulic conductivity, based on linear trend lines fitted to the water level data with the highest R-squared values, considered to represent the steady state. Relatively fresh, hard, silicified, unaltered, but strongly fractured rhyolite tuff was reached at a shallow depth (50 cm) in borehole No. 6. At this site the initial drop in the water level was very fast. Boreholes Nos. 3 and 4 contained only slightly different, strongly weathered, “sand-like” rhyolite tuff, in which feldspar minerals, which are easily modified, had been entirely transformed into clay, while some of the mafic minerals remained observable in the samples (mostly biotite). The hydraulic conductivity values of the strongly weathered, sand-like rhyolite tuff were lower than expected in the field, being several orders of magnitude lower than the conductivity of “true” sand and close to the values recorded for clayey loam. The results show that the presence of this kind of volcanic detritus in the soil profile leads to greater water retention, while silicified, fractured rhyolite that has undergone little or no alteration does not prevent the vertical movement of water. This means that terroir evaluation should take into account not only the nature of the underlying rock, but also to what extent it has been altered.