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Longer term monitoring of soil water content at a catchment scale is a key to understanding its dynamics, which can assist stakeholders in decision making processes, such as land use change or irrigation programs. Soil water monitoring in agriculturally dominated catchments can help in developing soil water retention measurements, for assessment of land use change, or adaptation of specific land management systems to climate change. The present study was carried out in the Pannonian region (Upper-Balaton, Hungary) on Cambisols and Calcisols between 2015 and 2021. Soil water content (SWC) dynamics were investigated under different land use types (vineyard, grassland, and forest) at three depths (15, 40, and 70 cm). The meteorological data show a continuous decrease in cumulative precipitation over time during the study with an average of 26% decrease observed between 2016 and 2020, while average air temperatures were similar for all the studied years. Corresponding to the lower precipitation amounts, a clear decrease in the average SWC was observed at all the land use sites, with 13.4%, 37.7%, and 29.3% lower average SWC for the grassland, forest, and vineyard sites, respectively, from 2016 to 2020 (measured at the 15 cm depth of the soil). Significant differences in SWC were observed between the annual and seasonal numbers within a given land use (p < 0.05). The lowest average SWC was observed at the grassland (11.7%) and the highest at the vineyard (28.3%). The data showed an increasing average soil temperature, with an average 6.3% higher value in 2020 compared to 2016. The grassland showed the highest (11.3 °C) and the forest soil the lowest (9.7 °C) average soil temperatures during the monitoring period. The grassland had the highest number of days with the SWC below the wilting point, while the forest had the highest number of days with the SWC optimal for the plants.

Summary. In this study, we presented the experience of two high-speed laser diffractometry methods for measuring particle size distribution (PSD) and microaggregate stability (MiAS%) of soils, which parameters have a significant influence on the soil water management properties. PSD results obtained with sieve-pipette and laser diffractometry method were compared on a continental (LUCAS), a national (HunSSD) and a regional (TOKAJ) database. We found significant differences between the results of the two methods at all three scales. When the clay/silt boundary was modified to 7 µm for the LDM, significantly better results were obtained. The LDM was also suitable for the determination of the MiAS% of soils, which was influenced mainly by organic matter, pH and exchangeable Na+ content of soils. Összefoglalás. Tanulmányunkban a lézerdiffraktométerrel végzett talajfizikai mérések tapasztalatait és alkalmazási lehetőségeit vizsgáltuk a vízgazdálkodási kutatásokban. A talajok mechanikai összetétele, azaz az elemi talajrészecskék méret szerinti százalékos eloszlása, az egyik legfontosabb talajfizikai paraméter, mely számos egyéb tulajdonságot, így a talajok szerkezetét, vízgazdálkodását befolyásolja. Meghatározása több módon történhet: pl. a hagyományos szitás-pipettás ülepítéses módszerrel (SZPM), vagy az egyik legmodernebbnek számító lézerdiffraktométeres (LDM) eljárással. Kutatásunk során e kétféle módszerrel kapott mechanikai összetétel eredményeket három nagyobb adatbázison hasonlítottuk össze: egy kontinentális (LUCAS), egy hazai (HunSSD) és egy regionális (TOKAJ) adatállományon. Azt tapasztaltuk mindhárom adatbázis esetében, hogy a lézerdiffrakciós vizsgálatok az agyagtartalmat alulbecslik a pipettás módszerrel kapott eredményekhez képest, míg a portartalmat felülbecslik (az adatsorok eltérését jellemző RMSE értékek az agyagfrakciókra: 16,30; 19,29 és 24,97; a porfrakciókra: 15,68; 19,82 és 26,95. A homoktartalmak közt lényegesen kisebb eltéréseket tapasztaltunk (RMSE: 7,26; 9,25 és 5,25 a három adatbázis esetében). Ha azonban az LDM vizsgálati eredményeknél módosítottuk az agyag és a por frakció mérethatárát 2 µm-ről 7 µm-re, szignifikánsan jobb eredményeket kaptunk az összehasonlítás során mind az agyagtartalom (RMSE: 8,99; 6,77 és 6,54), mind a portartalom esetében (RMSE: 8,87; 7,46 és 5,74). A különböző módszerekkel mért és számított PSD eredményeket textúra háromszög diagramokon is ábrázoltunk. A lézerdiffrakciós eljárás alkalmas a talajok mikroaggregátum stabilitásának (MiAS%) meghatározására is, melyet a HunSSD hazai adatbázis talajain mutattunk be. Megállapítottuk, hogy erős, szignifikánsan pozitív kapcsolat van a MiAS% és a talaj szervesanyag-tartalma között; és erős, szignifikánsan negatív kapcsolat a mikroaggregátumok stabilitása és a pH, a mésztartalom, a sótartalom és a kicserélhető nátriumtartalom között. A tanulmányban vizsgált talajfizikai tulajdonságok szorosan összefüggnek a talajok vízgazdálkodási tulajdonságaival. A talajok vízgazdálkodási tulajdonságait jellemző hidrofizikai paraméterek (víztartó képesség, vízvezető képesség) becslése általában a mechanikai összetétel adatok felhasználásával történik. A becslési módszerek (pedotranszfer függvények) pontosítására egyre gyakrabban figyelembe veszik a talaj szerkezeti tulajdonságait is. Amennyiben gyorsan és megbízhatóan tudjuk mérni a talajok mechanikai összetételét és aggregátum-stabilitását lézerdiffrakciós módszerekkel, akkor a hidrofizikai tulajdonságok becsléséhez szükséges input adatokat is gyorsan, nagyobb számban tudjuk előállítani, így a talajok vízgazdálkodását is több minta alapján, nagyobb részletességgel, megbízhatóbban tudjuk jellemezni.

The European Joint Programme Cofound on Agricultural Soil Management has set the goal of harmonizing national soil databases with the continental LUCAS topsoil database for the purpose of monitoring soil carbon, fertility and land degradation. Up-to-date soil surveys have poor spatial resolution and are very cost- and labour intensive, so harmonizing the existing datasets allows us to create more accurate soil maps with better resolution. The LUCAS topsoil database can be used to complement the Hungarian Soil Information and Monitoring System (SIMS) for the creation of more detailed soil-property maps. Due to the different laboratory analysis methods and sampling strategies used by the two databases, conversion was needed, so the datasets can be directly compared to each other and used together for digital soil mapping. Two sets of topsoil data were used from 2009 and 2015 from both LUCAS and SIMS respectively, so the swiftly changing soil properties (pH, CaCO3, OC, P, K) were available for a more accurate side-by-side comparison. Map products were created for the chemical soil properties of both the LUCAS and SIMS database with the ancillary data of 28 environmental covariates using random forest kriging with 10-fold cross-validation. The spatial resolution of the maps was 100 x 100 m. The raster maps were compared directly to each other using linear regression. In conclusion the results show that the LUCAS and national soil databases can and should be harmonized, merged and used together for creating more accurate soil maps with better spatial resolution at national and continental scale.

Within the TUdi project a comprehensive list of long-term monitored farms and experiments have been created in 2022, including basic data on the agricultural system, farm typology, soil and climate, and soil restoring strategies implemented for European TUdi partners (Austria, Bulgaria, Czechia, Hungary, Italy and Spain) and China. These data and results, in line with the objectives of the project, will contribute to the development of Decision Support Tools available to users to detect soil degradation and provide expert advice on mitigation. The TUdi database contains metadata, structured thematically, allowing insight into the data related to each experimental site (e.g. what purpose experiments are carried out or what type of data is generated in an experiment) and the implementation of queries according to the user's needs. At present, the TUdi meta-database contains the general description of 34 sites (farms and long-term experiment sites), and meta-information on different treatments, management (e,g. conventional, integrated, organic), tillage practices and different experimental settings of around 140 experiments related to these sites. A central element to which the other data are linked is the “site” under which the experiments are subdivided. A smaller part of the data is related to the site, while a larger part is related to the experiments. This is the structural element of the database, which cannot be modified in the future. This structure allows the database to be sufficiently flexible, both to add new sites and to add experiments or measured or calculated parameters that can be further linked to the sites. A query interface is also connecting to the TUdi Database webpage. The filtering options are focusing on the “Degradation threats/challenges” and the “Experiment type/treatment” options. The performance and effectiveness of the queries will be tested when the Partners upload their available experimental data into the system. According to the first query, concerning the main characteristics of the surveyed sites: 70% of the investigated sites are covered by annual crops, 7% are grasslands and the remaining 23% are orchards or olive plantations. 79% of the applied farming system is conventional, 10% organic, 4 % integrated, and the remaining 8% is a combination of them. Mineral fertilizers are used in 60% of the investigated sites, organic fertilizers in 32%, and their combination in the remaining 8%. Irrigation is applied on about one-third of the described sites (38%).Keywordssoil degradation, long term experiments, Decision Support Tool

Soil-plant-water monitoring allows stakeholders to obtain rapid information on plant stress caused by water or nutrient deficiencies. The main objective of the study was to investigate soil-plant-water interactions based on field measurements of plant reflectance and soil water content (SWC) under different land use types and inter-row managed vineyards. Four main study sites were investigated during the vegetation period: forest, grassland, cropland (sunflower), and vineyard. Three different soil management applications were studied in the vineyard: tilled (T), cover crops (CC), and grass (NT) inter-rows. SWCs were also measured within the row and between rows of vines to get a more complete picture of the hydrology of the sites. At each study site, we had several measurement points along a slope section, where each slope is prone to erosion. For continuous hydrological monitoring soil water and temperature sensors were placed 15 and 40cm below the ground at the top and bottom of the slopes. Normalized Difference Vegetation Index (NDVI) and Photochemical Reflectance Index (PRI) sensors were used to measure leaf reflectance. All sites included a set of hemispherical sensor sets. Topsoil SWC, leaf NDVI and chlorophyll concentrations, and Leaf Area Index (LAI) were measured every two weeks using hand-held instruments.Among the four land use types, the lowest SWC and soil temperature of the upper 20cm was observed in the forest, and the highest in the cropland. The in-row average topsoil SWCs and temperatures were lower in all study sites compared to the values measured in between rows. The lowest chlorophyll and NDVI values were observed in grassland, which also showed the highest drought stress. The grassed inter-row grapevines had significantly lower leaf chlorophyll contents than the other inter-row managed sites (p

Sustainability cannot be achieved without improving soil conditions. However, it is estimated that between 60 and 70% of EU soils are unhealthy. Thoughtful use of exogenous organic matter can help restore soil functions and thus improve soil health. Animal manures are the most abundant organic matter in agriculture and, in addition to their high nutrient content, they contribute to improving soil health in many ways by increasing soil biological activity. For these reasons, their efficient and environmentally friendly use is of major importance.The TUdi project will contribute to develop healthy and productive agricultural ecosystems, where the organic fertilizers play an important role in the nutrient supply of the plants. The ongoing development of the nutrient management tool has to consider the different behavior and characteristic of these materials. Our study gives an example of how the long term field trials results can be implemented in this process.37 trials have been selected from the database of the Hungarian field trials which contain the effects of farmyard manure and mineral fertilizer application on the basis of NPK nutrient equivalence. Among the various treatments, the yields of the absolute control, the farmyard manure treatment and the one with equivalent amounts of NPK in the form of mineral fertilizer were evaluated. The experiments were grouped according to the soil texture.Annual fertilization was more favourable in all cases than periodic manure application. Differences between yield surpluses declined with an increase of soil clay contents. The efficiency of fertilization in both farmyard manure and fertilizer treatments were higher on sandy soils, which have the poorest natural nutrient supplying capacity.The correlation between the changes in the organic matter (OM) content of the control plots soils, and differences of the responses to nutrient applied can be described by hyperbolic functions. A similar correlation was established between the AL—(ammonium lactate) soluble K contents and differences of the responses to farmyard manure and fertilizer.As the values of these two soil parameters increased, the advantage of the nutrients given in the form of fertilizer over farmyard manure declined. Keywords: long term field trial, manure application, fertilization, nitrogen use efficiency, nutrient advisory system

Microaggregates are structural elements of the soil smaller than 250 µm. These microaggregates are composed from diverse mineral, organic and biotic materials that are bound together during the process of pedogenesis (through a variety of ways and processes). According to the general theories, microaggregates are predominantly stabilized by organo-mineral complexes, which are relatively stable and are not easily degraded by changes in soil organic matter content as a result of land use and cultivation. At present, the relationship between soil processes and the formation of microaggregate stability needed further studies to gain a better understandingIn our study, we were looking for a quantifiable relationship between the stability of microaggregates and different soil reference groups and diagnostic properties. We examined 55 Hungarian soil profiles, which were selected on the basis of their various parameters. The stability of the microaggregate was determined by laser diffractometry (LDM) with a Malvern Mastersizer 3000, Hydro LV dispersion unit, as the ratio of dispersed to non-dispersed clay content. The measured data were sorted into a database and a statistical analysis were performed between the soils and WRB diagnostic properties of each reference group and the stability of the microaggregate. Based on our results, different significant soil groups could be identified, furthermore there is a good connection between the stability of the microaggregate and the soil reference groups. There is also a clear difference between the horizons of cultivated and uncultivated soils.This research is supported through the common grant of the Hungarian and Polish Academy of Sciences (Grant No. NKM-2019-17) and by the Hungarian National Research, Development and Innovation Office Foundation (Grant No. OTKA K 119475).

EJP SOIL, which is a European Joint Programme Cofund on Agricultural Soil Management, has posed questions concerning the application of various soil observation datasets to account, monitor and map agricultural soil carbon, fertility and degradation. One of the most exciting issue is, how the continental LUCAS Topsoil dataset and national soil observation/monitoring databases could be harmonized and/or should complement or improve each other to produce Europe wide spatial soil information to support European contribution towards international reporting on soils, and the accuracy of European agri-environmental policies. Methods are being searched by a broad international team. In our paper we present a countrywide case study for the comparison of (i) the representativity of the Hungarian Soil Information and Monitoring System (SIMS) versus LUCAS Topsoil dataset and (ii) some map products, which were modelled by the usage of the two reference data sources.The difference between national monitoring systems and LUCAS Topsoil dataset is mainly due to (i) the different measurement methods applied to determine soil properties, and (ii) the different sampling strategy, both in terms of sampling location and sampling depth. While transformation (using unit conversions, mass-preserving splines to derive soil properties for similar soil depth, pedotransfer functions for methods conversion, etc.) of the SIMS soil data into the units, methods and soil depth used in the LUCAS dataset could be carried out more or less straightforwardly, the spatial representativity, which strongly affects the performance of any digital soil map based on the given observation dataset, is a challenging feature, which could and should be checked.From a statistical point of view, a sample is said to be representative if it reflects the characteristics of the population the best. First we analysed whether the two sets of soil data represent the same population applying two approaches: by the comparison of (i) empirical cumulative distribution function and (ii) the mean values aggregated for different land use categories of the selected soil properties coming from the two system. Although based on the Kolmogorov-Smirnov test we could conclude that the Hungarian subset of the LUCAS Topsoil dataset and the data of the Hungarian Soil Information and Monitoring System come from the same population in the case of particle size distribution, pH, organic carbon and carbonate content, the land use based comparison did not give satisfying results.In the next round the countrywide spatial predictivity of the two datasets have been tested. Primary soil property map pairs have been compiled using the same ancillary datasets and digital mapping methods but the two different observation datasets. The two map products for the same property have been compared by both global measures and cell-to-cell statistics. In addition to pairwise comparison of basic statistical features (histograms, scatter plots), we have examined the spatial distribution of the differences. In our presentation our findings and experiences will be discussed. Acknowledgment: Our research was supported by the Hungarian National Research, Development and Innovation Office (NKFIH; K-131820), European Union’s Horizon 2020 Research and Innovation programme under grant agreement No. 862695.

Eutrophication, water quality and environmental status of lakes is a global issue that depends not only on the quality and quantity of nutrients stored in lake sediments but also on their relative content. On the example of Lake Balaton (Hungary), we jointly modelled the spatial distribution of the nutrients nitrogen and phosphorus, and their ratio (i.e. nitrogen to phosphorus ratio) in the sediments of the lake and then provided spatial predictions at different supports (i.e. point, basin and entire lake) with the associated prediction uncertainty. The objective of our study was to illustrate the merits of applying multivariate geostatistics when spatial modelling of more than one variable is targeted at various scales in water ecosystems. Exploratory variography confirmed that there is a spatial interdependency between the nutrients and therefore it is better to jointly model their spatial distribution. The results revealed that by the application of multivariate geostatistics the spatial interdependency existing between the nutrients under study can be explicitly taken into account and exploited in the course of spatial modelling to provide coherent and more accurate spatial predictions that could support the complex assessment of the water quality and environmental status of Lake Balaton. Besides, stochastic realizations reproducing the joint spatial variability of the two nutrients can be generated that allow to compute stochastic realizations of their ratio, furthermore, to provide spatially aggregated predictions for larger supports (e.g. basins or entire lake) with the associated prediction uncertainty, which may be better fit to the end-users' demands on spatially explicit information about sediment nutrients. Our study highlighted that it is worthy of applying multivariate geostatistics in case spatial modelling of two or more variables, which jointly vary in space, is targeted in water ecosystems. Acknowledgements: Our research was funded by the National Research Development and Innovation Office (NKFIH), grant number K-131820. The work of Gábor Szatmári was supported by the Premium Postdoctoral Scholarship of the Hungarian Academy of Sciences (PREMIUM-2019-390).

Over the last decades extensive work has been done on sampling optimization. Many of the related papers focused on the optimization of sampling for only one soil property. However, there is a necessity to prepare a sampling strategy which is optimized for multivariate digital soil mapping (DSM) purposes. The aim of our work was to elaborate a sampling optimization methodology for multivariate DSM considering the demands on economic efficiency. We presented and tested it through a real-time survey at Tokaj Wine Region, Hungary. The soil properties of interest were pH, soil organic matter (SOM), and calcium carbonate (CaCO3) content. The end-users defined the minimal requested precision for the DSM products (in terms of the average range of the 90% prediction interval), and priority areas on which more detailed survey was requested. We planned a two-phase soil survey based on regression kriging (RK). The results from the first-phase sampling were used to parameterize the second-phase sampling in which spatial simulated annealing (SSA) was applied. The spatially averaged range of the 90% prediction interval was the pre-survey quality measure which can be readily derived from the RK variance. The workflow can be summarized as follows: (1) rank the soil properties considering their spatial variabilities, and precision requests, (2) optimize the sampling design by SSA for the dominant soil property, (3) optimize the sampling by the invers application of SSA for the next soil property using the optimized design from the previous step, and (4) repeat the previous step until all soil property are being selected. In our case, SOM was the dominant property. According to the plot of the sample size vs. quality measure, the optimized design with 500 samples will ensure the minimal requested precision for the SOM map (i.e. 0.5%). In the next step, the optimal removal of those sampling points was targeted which have less information content. In the cases of pH and CaCO3, 100 and 175 could be removed from the 500 samples, and the remaining 400 and 325 samples will ensure the requested precision for the pH (i.e. 1.2) and CaCO3 (i.e. 5%) maps. We computed the relative sampling density on priority and non-priority areas for each sampling designs which showed that densities on priority areas were at least 1.5 times higher than on non-priority areas. We could conclude that the methodology is able to optimize the sampling design for multivariate DSM purposes considering numerous sampling constraints such as the predefined precision, priority areas, and economic efficiency.

Optimal water supply of plants is key to high yields. However, irrigation in drier regions must be accompanied by soil conservation. Nationwide planning of irrigation needs spatially exhaustive, functional soil maps, which may support proper recommendations for the different areas. For supporting the Hungarian national irrigation strategy, a series of countrywide functional soil maps was created, which reveal the pedological constraints, conditions and circumstances of irrigation by the spatial modelling of the relevant functional features of the soil mantle. Irrigation can improve productivity, while its negative effects may lead to soil degradation. This paper focuses on threats, the spatial identification of potentially affected areas. The thematic maps spatially model the irrigability and vulnerability of soils. Estimation of salt accumulation hazard, and soil structure degradation risks were targeted. The salinization hazard assessment was carried out by two ways. We applied the steady state concept of critical water-table depth and a more dynamic, process-based method. To estimate soil structural degradation hazard, class-based relationships were developed based on soil profile data of MARTHA 1.0 (Hungarian Detailed Soil Hydraulic Database). Soil type, organic matter content, carbonate content, soil reaction and texture class (USDA) were taken into consideration to develop pedotransfer functions for modelling the correlations between primary soil properties and threats indicators. The new maps can help decision makers to improve land use management, and sustainable agronomy.

Összefoglalás A klímaváltozás hatására várhatóan nem csak a csapadék éves mennyisége, hanem az éven belüli eloszlása is változik, egyidejűleg megváltozhat annak az időszaknak a hossza, amelyben a talajok vízbefogadásra képesek. A talajnedvesség és csapadék idősoros adatok alapján vizsgálhatjuk a változó környezetei feltételek hatását a talajok vízgazdálkodására. Jelen tanulmányban 2017. június–2018. május közötti időszakban a talajnedvesség-tartalom alakulását vizsgáltuk két eltérő domborzati adottságú szelvényben (teraszon és lejtőn) a tokaji Nagy-hegy déli lejtőjén elhelyezkedő Szarvas-dűlő szőlőültetvényen. Összehasonlítottuk a két mérőhely talajnedvességforgalmát, valamint vizsgáltuk a csapadékesemények hatását. A teraszon lévő szelvény a csapadék jellemzően 65–99%-át közvetlenül befogadta, míg azonos csapadékeseményekre nézve ez az érték a lejtőn, az intenzívebb felszíni párolgás, valamint a felszíni lefolyás miatt csak 30–80%, szélsőséges esetben ennél is kisebb volt. Az egyes rétegekben mért nedvesség profilok adataiból következtettünk a beszivárgás dinamikájára, a vízáteresztés mértékére. Azt tapasztaltuk, hogy telített állapotú szelvény esetén a terasz erősen tömődött rétege a vártnál kevésbé akadályozta a nedvesség mélyebb rétegek felé terjedését. A teraszon lévő szelvény a tömődött rétegek ellenére összességében kedvezőbb vízháztartást biztosított, mint a meredek lejtő. A lejtő kedvezőtlen vízháztartását részben a nyári erőteljes párolgás, részben az egész évben jelentős felszíni lefolyás okozta. A szelvények vízkészletét 120 cm mélységig összegezve megállapítottuk, hogy a terasz teljes vízkészlete a vizsgált időszakban átlagosan több mint 20%-kal meghaladta a lejtőn feltárt szelvényét. Ez a különbség a nyári hónapokban 90–108 mm víztöbbletet jelentett a teraszon, a hasznosítható víz arányában kifejezve 62–88 mm-t. Nyáron, az eltérő száradás miatt augusztus végén volt a legnagyobb a terasz nedvességtöbblete (114 mm-rel), míg a téli–tavaszi időszakban az eltérő intenzitású feltöltődés okozott különbséget (legnagyobb eltérés: 159 mm). A vízkészletek téli–tavaszi feltöltődése szempontjából más-más időszakra volt érzékeny a két szelvény. A terasz fagymentes időszakban, december végére gyakorlatilag elérte a maximális vízkapacitását, s ezt kisebb ingadozásokkal megtartotta április elejéig, melyet a február–márciusi fagyos időszak sem befolyásolt. A lejtő szelvénye fokozatosan töltődött fel, vízkészlete december közepétől a jellemzően fagyveszélyes január–februári időszakban is növekedett, majd április elejére „tetőzött”, 30 mm-re megközelítve a terasz vízkészletét. A feltöltődés menetében tapasztalt eltérés azt mutatja, hogy a terasz vízkészlete a korai feltöltődés miatt nem érzékeny a jellemzően fagyos február–márciusi időszakra. A lejtő vízkészletének feltöltődése azonban jóval belenyúlik a potenciálisan fagyos időszakba, vízkészletének alakulását a fagyos napok számának változása jobban befolyásolja.

Összefoglalás Tanulmányunkban 27 különböző hazai talajszelvényben vizsgáltuk, hogy a talajok N2-BET fajlagos felületét mely talajtulajdonságok milyen mértékben befolyásolják. Az egytényezős elemzések alapján elmondható, hogy a talajok mechanikai összetétele mutatja a legszorosabb kapcsolatot a fajlagos felülettel, az agyagtartalommal szoros pozitív kapcsolat van, ugyanakkor a homoktartalom növekedésével a fajlagos felület csökken. Igazolható a mész- és humusztartalom negatív előjelű nem túl szoros kapcsolata is a N2-BET felület értékekkel. A korrelációs vizsgálat gyenge pozitív kapcsolatot mutat a Hargitai-féle humuszstabilitási mutatóval. A talaj kémhatása és fajlagos felület közötti kapcsolatot nem tudtuk igazolni. Vizsgáltuk a különböző talajtulajdonságok együttes hatását is a talaj N2-BET fajlagos felületére, valamint a talajok főtípusának, illetve a talajtípusoknak a szerepét. A teljes adatbázis alapján a N2-BET fajlagos felület kialakításában a legfontosabb tényezők az agyagtartalom, majd a humusztartalom, végül a mésztartalom. Amennyiben a talajok humuszanyagainak minőségéről is rendelkezünk információkkal, akkor az agyagtartalom, a humusztartalom, a humuszminőség és kémhatás azok a talajtulajdonságok, amelyek elsősorban felelősek a talajok a N2-BET fajlagos felületének kialakításáért. Megállapítottuk, hogy a fajlagos felületet becslő modellek pontossága tovább javítható a talajok rendszertani besorolásának (főtípus, típus), mint kategóriaváltozónak figyelembevételével. A talajok rendszertani helyének ismerete ugyanis számos olyan talajjellemzőről, azok együttes hatásairól nyújt közvetett információt, melyekről egyébként nem rendelkezünk közvetlen mérési eredménnyel.

Greenhouse gas (GHG) emissions from agricultural soils can accelerate climate change, therefore, different soil fertilization techniques should be assessed before application to reduce GHG emissions. Pig slurry applications can greatly influence soil carbon dioxide (CO2), nitrous oxide (N2O), and ammonia (NH3) emissions of arable fields; thus, it is important to find site-specific techniques to lessen any negative environmental impacts. In this study, we examined the short-term effect of pig slurry application techniques of spreading and injection on soil greenhouse gas and NH3 emissions under different irrigation amounts. We used the dynamic chamber method with in-situ gas analyzers. Our study showed that there were elevated emissions during the first week after slurry application; however, the difference between GHG emissions of spreading and injection treatments were not significant. Elevated GHG emissions (213–338% and 250–594% in the case of CO2 and N2O emissions, respectively) were observed under dry circumstances compared to irrigated treatments, as well as significantly higher NH3 emissions occurred for surface spreading under non-irrigated (dry) circumstances compared to other treatments. There were no statistically significant differences between the soil chemistry of different application techniques. However, pig slurry increased the available nitrogen forms (ammonium- and nitrate-nitrogen), which caused N2O and NH3 peaks regardless of treatment type. Leachate chemistry was more affected by irrigation strategies than application techniques. Our study highlights the importance of soil conditions at the time of application, rather than the application technique for fertilization using pig slurry.

Tillage practices influence soil CO2 emissions, hence many research investigate the long-term effects of conservation and conventional tillage methods e.g. ploughing and no-tillage on soil greenhouse gas emission.The experiment site is an 18-years-old long-term tillage trial established on chernozem soil. During 2020, we took weekly CO2 emission measurements in the mouldboard ploughing (MP), no-tillage (NT), and shallow cultivation (SC) treatments Tillage depth was 26-30 cm, 12-16 cm and 0 cm in the cases of MP, SC and NT respectively. The experiment was under wither oat cultivation.We investigated the similarity in the CO2 emission trends of SC to MP or NT treatments. Besides CO2 emission measurements, we also monitored environmental parameters such as soil temperature (Ts) and soil water content (SWC) in each treatment.During the investigated year (2020 January - December) SC had higher annual mean CO2 emission (0.115±0.083 mg m-2 s-1) compared to MP (0.099±0.089 mg m-2 s-1) and lower compared to NT (0.119±0.100 mg m-2 s-1). The difference of the CO2 emissions was significant between SC and MP (p0.05) treatments. The Ts dependency of CO2 emission was moderate in all treatments. CO2 emissions were moderately depended on SWC in MP and SC, and there was no correlation between these parameters in NT.The annual mean CO2 emission of the SC treatment was more similar to the NT, than to the MP treatment.

Recently, FAO and Global Soil Partnership (GSP) launched the Global Map of Salt-affected Soils (GSSmap) international initiative, which pursued a country-driven approach and aimed to update the global and country-level information on salt-affected soils (SAS). The objective of our study is to present how Hungary contributed to this international initiative by preparing its own SAS maps according to the GSSmap specifications. For this purpose, we used not just a combination of advanced machine learning and multivariate geostatistical techniques for predicting the spatial distribution of the selected SAS indicators (i.e., pH, electrical conductivity and exchangeable sodium percentage) for the topsoil (0–30 cm) and for the subsoil (30–100 cm), but also a number of image indices exploiting a huge amount of relevant information contained in Sentinel-2 satellite images. The importance plots of random forests showed that in addition to climatic, geomorphometric parameters and legacy soil information, image indices were the most important covariates. The performance of spatial modelling of SAS indicators was checked by 10-fold cross validation showing that the accuracy of the SAS maps was acceptable. By this study and by the resulting maps of it, we not just contributed to GSSmap, but also renewed the SAS mapping methodology in Hungary, where we paid special attention to modelling and quantifying the prediction uncertainty that had not been quantified or even taken into consideration earlier. Acknowledgment: Our research was supported by the Hungarian National Research, Development and Innovation Office (NKFIH; K-131820 and K-124290) and by the Premium Postdoctoral Scholarship of the Hungarian Academy of Sciences (PREMIUM-2019-390) (Gábor Szatmári).

Three slopes with grapevines were investigated to see changes in the soil-plant-water system over vegetation growth. The slopes have the following parameters: 1) young grapevine plants with tilled soil (YR), 2) older grapevines with grassland between rows next to the young grapevine (OR), and 3) older grapevines with grass between rows at a different location and slope position (OF). All experimental slopes had identical plant canopy management such as pruning or shoot and bunch thinning. All slopes are prone to erosion. For continuous hydrological monitoring soil water content and temperature sensors were placed at 15 cm and 40 cm below ground both at the top and bottom of the slopes. For indications of plant growth photosynthetically active radiation (PAR) sensors were placed below the canopy, and Normalized Difference Vegetation Index (NDVI) and Photochemical Reflectance Index (PRI) sensors were used to monitor leaf reflectance. All sites included a set of hemispherical sensor sets to measure incoming radiation. Leaf Area Index (LAI) was measured on a biweekly basis using a handheld ceptometer. We found that in the OR and OF sites the soil water content (VWC) was higher at the lower portion of the slope, while for the YR the VWC was the highest at the top. Soil temperature was higher at the top of the slopes over 6% for YR and 9% for OR sites compared to the bottom measuring points. The most notable difference in the NDVI values was observed for OR, where the plants at the top of the slope showed much lower NDVI values compared to the ones at the bottom of the slope. For the younger grapevines, this tendency was showing the opposite results, the plants at the top of the slope had much higher NDVI values than the lower ones, indicating higher leaf densities. The collected PAR values further support these findings, as the OR plants at the top of the slope had the highest PAR values signifying lower leaf areas and densities. The differences in the PRI values suggest that plants at the bottom of the slope have either better nutrient usage or less stress for drought conditions. The LAI values correlated well with the spectral reflectance sensor data. The OR and OF showed higher LAI at the bottom of the slope, while the younger grapevines showed the opposite. The highest LAI values were observed for the YR (max values were around 7) and the lowest for the OF plants (max LAI value was 3.2).

Soil respiration is a significant contributor to the global emissions of CO2 and is governed by many soil factors. Reliable estimates of CO2 emission on different scales (e.g., field, regional level) are hard to obtain due to the expressed spatial and temporal variability of the CO2 flux. This study aims to investigate the spatial variability of CO2 flux and soil properties in soybean cropland on Fluvisols (Croatia). The field measurements and soil samples were taken in a regular sampling grid (2 × 2 m) with 44 points in total and the spatial variability was assessed using the kriging and cokriging techniques. The soil CO2 flux showed relatively high spatial heterogeneity, ranging from 0.03 mg/m2s to 0.40 mg/m2s. The soil organic matter content (SOM), soil water content (SWC), and soil temperature (ST) had the lower variability ranging from 2.09% to 2.52%, from 27.7% to 46.8%, and from 13.7 °C to 18.2 °C, respectively. The spatial dependence was high for CO2 flux and ST, moderate for SOM, and low for SWC. The incorporation of the auxiliary variables increased the precision of the estimations for CO2 flux, SOM, and SWC. Kriging was the most accurate method for the spatial prediction of ST. The SWC was associated as the most important factor of the CO2 fluxes, indicated by their significant negative correlation, and the highest increase of the prediction precision during spatial modeling. However, more robust co-variates should be incorporated in future models to further increase the precision., A talajlégzés, melyet számos talajtulajdonság befolyásol, jelentősen hozzájárul a globális CO2 emisszióhoz. A CO2 emisszió különböző léptékű, megbízható becslése nehéz, annak nagyfokú térbeli és időbeli változékonysága miatt. Kutatásunk célja a CO2 kibocsátás és különböző talajtulajdonságok térbeli változékonyságának vizsgálata egy horvátországi szója ültetvényben, Fluvisol talajon. Az in-situ méréseket, valamint a talajminták gyűjtését egy 2x2 méteres rácsháló 44 pontjában végeztük el, a térbeli változékonyság kimutatásához krigelést és kokrigelést használtunk. A talaj CO2 kibocsátása relatív nagy térbeli változékonyságot mutatott, az értékek 0.03 és 0.40 mg m-2 s-1 között alakultak. A talaj szerves anyag tartalmának (SOM), nedvesség tartalmának (SWC) és hőmérsékletének (ST) változékonysága kisebb volt, ezek értékei 2.09 és 2,52%, 27.7 és 46.8%, valamint 13.7 és 18.2 ºC között változtak. A talaj CO2 kibocsátását nagymértékben meghatározta a mérési pontok térbeli helyzete, a SOM közepes, az SWC pedig alacsony térbeli függést mutatott. A segédváltozók modellbe való beépítése növelte a CO2 kibocsátás, valamint a SOM és a SWC becslésének pontosságát. A SWC volt legnagyobb hatással a CO2 kibocsátás alakulására, e két változó között negatív szignifikáns összefüggést találtunk, valamint ez okozta a legnagyobb növekedést a becslés pontosságában a térbeli modellezés során. A továbbiakban robusztusabb segédváltozó adatsorok felvétele szükséges a pontosság növelése érdekében.

Soil physical properties and soil water regime have been in the focus of soil surveys and mapping in Hungary due to their importance in various environmental processes and hazards, like waterlogging and drought, which endanger extended areas. In the late ‘70s a category system was elaborated for the planning of water management, which was used as the legend of a nationwide map prepared at a scale of 1:500.000. Soils were characterized qualitatively (e.g.: soil with unfavorable water management was defined with low infiltration rate, very low permeability and hydraulic conductivity, and high water retention), without quantification of these features. The category system was also used for creating large-scale (1:10.000) water management maps, which are contained legally by expert’s reports prepared on the subject of drainage, irrigation, liquid manure, sewage or sewage-sludge disposal. These maps were prepared eventually, essentially for individual plots and are not managed centrally and are not available for further applications.Recently a 3D Soil Hydraulic Database was elaborated for Europe at 250 m resolution based on specific pedotransfer functions and soil property maps of SoilGrids. The database includes spatial information on the soil water content at the most frequently used matric potential values, saturated hydraulic conductivity, Mualem-van Genuchten parameters of the moisture retention and hydraulic conductivity curves. Based on similar idea, the work has been continued to produce more accurate and spatially more detailed hydrophysical maps in Hungary by generalizing the applied pedotransfer functions and using national soil reference data and high resolution, novel, digital soil property maps.We initiated a study in order to formalize the built-in soil-landscape model(s) of the national legacy map on water management, together with the quantification of its categories and its potential disaggregation. The relation of the legacy map with the newly elaborated 3D estimations were evaluated at two scales: nationwide with 250 m resolution and at catchment scale with 100 m resolution. Hydrological and primary soil property maps were used as predictor variables. Unsupervised classifications were performed for spatial-thematic aggregation of the soil hydraulic datasets to identify their intrinsic characteristics, which were used for the elaboration of a renewed water management classification. Hydrological interpretation of the categories provided by the optimum classifications has been carried out (i) by their spatial cross-tabulation with the categories of the legacy map and (ii) using the interval estimation of the applied soil hydraulic properties provided for the individual water management categories. Machine learning approaches were used to analyze the information content of the legacy maps’s category system, whose results were used for its disaggregation. Conditionally located random points were sequentially generated for virtual sampling of the legacy map to produce reference information. The disaggregated maps with the legend of the traditional water management classes were produced both on national and catchment level.Acknowledgment: The research has been supported by the Hungarian National Research, Development and Innovation Office (NRDI) under grants KH124765, KH126725, the János Bolyai Research Scholarship of the Hungarian Academy of Sciences and the MTA Cloud infrastructure (https://cloud.mta.hu/).

The aim of this study was to investigate the spatial heterogeneity of CO2 emission of two different croplands in Croatia (Šašinovec, 45° 50´ N; 16° 11´ E; soil type - Stagnosols) and in Hungary (Józsefmajor, 47° 40´ N; 19° 36´ E; Chernozems). The measurements of the soil water content (SWC), soil temperature (Ts), organic matter (OM) and CO2 flux was executed after the harvest of the soybean in both fields. In a regular grid (2 x 2 m and 2 x 3 m) 44 and 170 samples were collected from Croatian and Hungarian site, respectively. At Hungarian site Ts and SWC showed relatively high spatial heterogeneity, ranging from 19.4 to 24.6 oC, and from 7.5 to 34.1%, respectively. Content of soil OM had lower variability ranging from 2.0 to 2.4 % at Croatian and from 3.2 to 4.5 % at Hungarian site, respectively. CO2 efflux was 0.125 ± 0.078 and 0.060 ± 0.088 mg m- 2 s-1 in average at Croatian and Hungarian field, respectively. Investigated properties did not follow normal distribution, so logarithm transformation were applied before modelling. Kriging interpolation model for mapping soil properties is tested to compare the prediction accuracy. Soil maps showed sufficient concentrations of soil OM at Hungarian site and insufficient concentrations of OM at Croatian site. Soil CO2 efflux map showed that the largest part of the investigated area in Hungary have low loss of C, while loss of C at Croatian site is high. There are areas, especially wheeled rows, where CO2 emission is lower than the average value of the field at both investigated site. These low CO2 emission areas coincide with the compacted row of wheel tracks. For future management it is necessary to provide better conditioning of soil at Croatian site and adopt environmental friendly soil management at both sites. This work is supported by the Croatian-Hungarian Bilateral Project (2018-2.1.12-TÉT-HR-2018-00007) and the PD116084 and NKFIH131792 reseach project.

Land use and management affect soil hydrological processes, and the impacts can be further enhanced and accelerated due to climate change. In this study, we analyzed the possible long-term effects of different land use types on soil hydrological processes based on future climatic scenarios. Soil moisture and temperature probes were installed at four land use sites, a cropland, a vineyard, a meadow, and a forest area. Based on modeling of long-term changes in soil water content (SWC) using the HYDRUS 1D model, we found that changes in precipitation have a more pronounced effect on soil water content than changes in air temperature. Cropland is at the highest risk of inland water and SWC values above field capacity (FC). The number of days when the average SWC values are above FC is expected to increase up to 109.5 days/year from the current 52.4 days/year by 2081–2090 for the cropland. Our calculations highlight that the forest soil has the highest number of days per year where the SWC is below the wilting point (99.7 days/year), and based on the worst-case scenario, it can increase up to 224.7 days/year. However, general scenario-based estimates showed that vineyards are the most vulnerable to projected climate change in this area. Our study highlights the limitations of potential land use change for specific agricultural areas, and emphasizes the need to implement water retention measures to keep these agricultural settings sustainable.

Eutrophication, water quality, and environmental status of lakes is a global issue that depends not only on external loadings from industrial, agricultural, and municipal sources but often also on internal loadings from lake sediments. In the latter case, in addition to the quality and quantity of nutrients stored in sediments, their relative content may be an important factor. In the example of Lake Balaton, we jointly modeled the spatial distribution of the nutrients nitrogen (N) and phosphorus (P) and their ratio (i.e., N:P) in the sediments of the lake and then provided spatial predictions at different scales (i.e., point, basin, and entire lake) with the associated uncertainty. Our aim was to illustrate the merits of applying multivariate geostatistics when spatial modeling of more than one variable is targeted at various scales in water ecosystems. Variography confirmed that there is a spatial interdependence between the nutrients. The results revealed that multivariate geostatistics allows this interdependence to be taken into account and exploited to provide coherent and accurate spatial models. Additionally, stochastic realizations, reproducing the joint spatial variability, can be generated that allow providing spatially aggregated predictions with the associated uncertainty at various scales. Our study highlighted that it is worthy of applying multivariate geostatistics in case spatial modeling of two or more variables, which jointly vary in space, is targeted in water ecosystems.

Traditionally in Hungary the soil cover under agricultural and forestry management is typically characterized independently and just approximately identically. Soil data collection is carried out and the databases of soil features are managed irrespectively. As a consequence, nationwide soil maps cannot be considered homogeneously predictive for soils of croplands and forests, plains and hilly/mountainous regions. In order to compile a national soil type map with harmonized legend as well as with spatially relatively homogeneous predictive power and accuracy, the authors unified their resources. Soil profile data originating from the two sources (agriculture and forestry) were cleaned up and harmonized according to a common soil type classification. Various methods were tested for the compilation of the target map: segmentation of a synthesized image consisting of the predictor variables, multi stage classification by Classification and Regression Trees, Random Forests and Artificial Neural Networks. Evaluation of the results showed that the object based, multi-level mapping approach performs significantly better than the simple classification techniques. A combination of best performing classifiers, when each classifier's vote on the same object is weighted according to its confidence in the voted class, led to the final product: a unified, national, soil type map with spatially consistent predictive capabilities.

The particle size distribution (PSD) values obtained for a soil database representing the main Hungarian soil types using the Hungarian standard (MSZ-08-0205-78) and the international standard (ISO/DIS 11277:1994) were compared with the pipette method. The relationship between these PSDs and other physical soil characteristics (upper limit of plasticity according to Arany, water vapour adsorption according to Sík) was also analysed, and a suggestion was made of how these results could be converted into each other. Experience showed that the pre-treatments applied as part of the ISO/DIS method may change the ratio of particle size fractions: there was a significant increase in the clay content, while the silt content decreased to a lesser and the sand content to a greater extent, possibly because some of the particles remain in microaggregate form when the MSZ method is used. The results confirmed the greater accuracy of the ISO/DIS method: the clay contents measured with the ISO/DIS method exhibited stronger correlations with the upper limit of plasticity according to Arany and with hygroscopicity values than those measured with the MSZ method. The estimated ISO/DIS fractions became much closer to the measured ones when the suggested pedotransfer functions were applied. The conversion method proved to be more reliable for the prediction of clay and sand content than for silt content. In its present form the estimation method is not suitable for replacing the ISO/DIS method, but it could be of good service in research and comparative analysis in cases where only the MSZ method can be used or where only old MSZ PSD data exist.

Catchment scale hydrological models are promising tools for simulating the effect of catchment-specific processes and management on soil and water resources. Here, we present a model intercomparison study of runoff simulations using three different semi-distributed rainfall-runoff catchment models. The objective of this study was to demonstrate the applicability of the Hydrologiska Byrans Vattenavdelning (HBV-Light); Precipitation, Evapotranspiration and Runoff Simulator for Solute Transport (PERSiST); and INtegrated CAtchment (INCA) models on Somogybabod Catchment, near Lake Balaton, Hungary. The models were calibrated and validated against observed discharge data at the outlet of the catchment for the period of January 1, 2006 -July 12, 2015. Model performance was evaluated using graphical representations, e.g. daily and monthly hydrographs and Flow Duration Curves (FDC) and model evaluation statistic; Nash-Sutcliffe efficiency (NSE) and coefficient of determination (R2). The simulation results showed that the models provided good estimates of monthly average discharge (0.60-0.90 NSE; 0.60-0.91 R2) and satisfactory results for daily discharge (0.46-0.62 NSE; 0.50-0.67 R2). We found that the application of hydrological models serves as a powerful basis for ensemble modelling of average runoff and could enhance our understanding of the eco-hydrological and transport processes within catchments. On the other hand, it can highlight the uncertainty of model forecasts and the importance of goal specific evaluation.

This paper analyses the drought-induced growth responses of two ecologically and economically important broadleaf tree species, namely sessile oak (Quercus petraea (Matt.) Liebl.) and Turkey oak (Quercus cerris L.) in south-western Hungary. Although both have been described as drought‐tolerant species, our understanding of their growth responses to drought extremes is still limited. Forest stands of younger ages of the target species were sampled along a precipitation gradient under similar soil conditions. 136 tree-ring samples were used to build six species- and site-specific chronologies. We also applied several dendroecological metrics to assess the drought sensitivity of the species. Water deficit was estimated by various drought indices including the soil water-budget based water stress index. The results indicated a strong dependency of annual tree-ring width of both species on the water availability of summer months in the actual year of ring formation. However, we found markedly different reaction of the two species against drought conditions. Turkey oak responded more sensitively to droughts than sessile oak revealed by the significantly lower resistance and higher recovery potential of this species. The more plastic behaviour of Turkey oak could be also perceived by the higher sensitivity of its tree-ring chronologies and by the observed relationship between resistance and recovery that showed a closer fit to the line of full resilience in case of this species. Regarding the precipitation gradient, a linearly proportional increase of growth reduction with rising water stress was found for Turkey oak while the growth response of sessile oak decreased considerably with increasing aridity indicating lower growth plasticity of sessile oak to droughts there. Based on our findings it seems that Turkey oak copes better with droughts than sessile oak and may gain competitive advantages under the projected climate change in Hungary.

With the ongoing DOSoReMI.hu project we aimed to significantly extend the potential, how soil information requirements could be satisfied in Hungary. We started to compile digital soil maps, which fulfil optimally general as well as specific national and international demands from the aspect of thematic, spatial and temporal accuracy. In addition to relevant and available auxiliary, spatial data themes related to soil forming factors and/or to indicative environmental elements we heavily lean on the various national soil databases. The set of the applied digital soil mapping techniques is gradually broadened. In our paper we present some results in the form of brand new soil maps focusing on the territory of Hajdú-Bihar county.

A kovaval atitatott, alig mallott riolittufat feltaro furasban elenk vizmozgas volt megfigyelhető a fizikai aprozodas soran felnyilt kőzetrepedeseknek koszonhetően, a meresek alapjan szamolt hidraulikus vezetőkepessege a valyog–homokos valyog fizikai talajfelesegű szintekehez hasonlo. A megjelenese alapjan „vulkani homok”-kent aposztrofalt, mallott riolittufa viz-vezető kepessege az előzetesen vartnal kisebb volt, nagysagrendekkel maradt el a „tenyleges” homok vezetőkepessegetől, megjelenese jelentősen lelassitotta a szel-venyekben tapasztalt vizmozgast; szamolt hidraulikus vezetőkepessege nagysag-rendileg az agyagos valyogehoz all kozel. A tapasztalt jelenseg oka egyreszt az, hogy a mallas soran a kőzetrepedesek eltomődtek, eltűntek, masreszt pedig az, hogy a mallott agyagos resz a durvabb szemcsejű „mallasi maradek” porusterebe uleped-ve a nedvessegmozgas szamara rendelkezesre allo porusteret jelentősen lecsokken-tette. Az eredmenyek azt jelzik, hogy a szőlőteruletek termőhelyi adottsagait meghata-rozo ...

In this research we present the first results how can be used laser diffraction measurement in soil physics practice. The main goals are understanding differences of particle size distribution (PSD) measurments, developing converting methods of PSD data of different determinations. In order to realization of this survey a representative soil database of Hungarian soil types was built up. We compared PSDs of 157 soil samples measured with sieve-pipette method (SPM) and laser diffractometer technique (Malvern Mastersizer 2000) (LDM). Soil textural classes were also determined using the USDA texture triangle. We used the clay/silt fraction boundary values (clay < 0.0066 mm; silt: 0.0066 - 0.05 mm) introduced for the LDM data in order to take them comparable to PSD data determined by the SPM: We got higher similarities of clay and silt fractions of the modified size boundary values. For the used dataset correspondence of texture classes derived from SPM and LDM PSD data, however is not higher than 60%.

A Duna–Tisza közi hátságban az elmúlt évtizedekben jelentős változások zajlottak le a terület hidrológiai viszonyaiban történt változások miatt. A hátság egyik legérzékenyebb természeti képződményei a szikes tavak. Ezek állandóságához nem csupán megfelelő vízellátottság, de megfelelő mennyiségű és minőségű oldható só is szükséges. A hátságban zajló regionális és lokális vízforgalom tér- és időbeli koncepcionális modellje alapján, a Szappanostó példáján számszerűen jellemeztük az elmúlt 31 év folyamán a talajok sótartalom-változását. Ehhez négy, 1983-ban már vizsgált mintapontban a talajvíz szintjét, összetételét és a talajt is elemeztük — lehetőség szerint ugyanolyan módszerrel. A területen a talajvízszint süllyedt és a felszíni vízborítás jelentősen csökkent, valamint csökkent a talajvíz sótartalma, lúgossága és nátriumtartalma. A talaj felszínközeli rétegeiben csökkent a sótartalom, a pH és a nátriumtartalom. A CaCO3-tartalom mélységi lefutási görbéi átrendeződtek, ebben a kilúgzás mellett a tómederben és a partján működő ráhordás/lehordás is jelentős szerepet játszhatott. A tómedret teljesen benőtték a növények, az 1983-ban jellemző sókedvelő, nagy sótartalmat is tűrő növényekhez képest 2014-re a kis talajsótartalmat kedvelő növé-nyek terjedtek el, teljesen beborítva a felszínt. Megnövekedett a talaj humusztartal-ma és kiterjedt a füvek kaszálása.

A felszíni földtani képződmények talajképződési szempontból történő értékelése gyakorlati célú közelítés, amely a területen legvalószínűbben előforduló talajképző kőzet leírását szolgálja. A talajtani felvételezések hazai adatbázisokban elérhető, talajképző kőzet adatai a sík- és dombvidéki mezőgazdasági területeken sűrűsödnek, azonban tematikusan nem részletesek és kevés osztályt jelenítenek meg. A Magyar Állami Földtani Intézet 1:100.000-es méretarányú földtani térképének (FDT100) adatai jól hasznosíthatók a talajképző kőzet (talajképző üledék) jellemzésére, ha az arra utaló tartalmi elemeit a FAO-rendszer nevezéktanának alkalmazásával egységesen kezeljük. A földtani térképen jelölt képződmények litológia és fácies szerinti leírása, több-kevesebb egyszerűsítéssel lehetővé teszi a talajképző kőzetekre alkalmazott FAO-féle hierarchikus rendszerbe illesztést. A korreláltatott FDT100 képződményeket középtájanként áttekintve megállapítható, hogy azok elterjedése az eddigi ismereteinknek nem mond ellent, sőt esetenként a tájegységek specifikumait jobban kiemelő részleteket hangsúlyoznak. A tematikai felbontás növelése lehetőséget ad a talajképző kőzetnek az AGROTOPO Adatbázisban foglaltnál részletesebb leírására.Az AGROTOPO térkép poligonjai geometriailag sok helyen erősebben generalizáltak, mint a FDT100-ban feltüntetett képződményhatárok. Ennek viszonylag könnyű és gyors feloldását jelentheti a nagyobb poligonok felbontása (lásd Pásztor et al., 2013), de leginkább a megfeleltetett talajképző kőzet tematikát is magába foglaló, digitális térképezési alapokon megújított „agrotopográfiai” jellegű térkép létrehozása mutat a megoldás felé. A jelenleg is tőzegesként számon tartott, de valójában már átalakult területeken új térképi adatforrások bevonása is szükséges.

A mathematical model was applied for the Bukk Mountains (Hungary) to evaluate the effects of climate change on soil water balance elements and soil water regime. Model runs using SWAP model were performed for combinations of four distinctive soil types and three land use systems of arable land, grassland, and forest. The temporal variation of soil water regime under changing climatic conditions was examined considering no land cover change occurring in the future. The climate data consisted of the predictions of two regional climate models, the Swiss CLM and the Swedish RCA. The RCA results showed 45% to 50% and the CLM showed 5% to 14% higher future precipitation outlook compared to present conditions. Considering different land use types, the projected number of days with soil moisture deficit was the highest in forest ecosystems for both the upper 50 cm soil layer and the whole soil profile, which could be as high as 61% of days below optimal soil water content range. Our results showed increased water fluxes, especially in deep percolation in far future period and a strong influence of soil properties on the changes in the climate model results, indicating significant long-term effects of climate change on soil water regime.

The main objective of the DOSoReMI.hu (Digital, Optimized, Soil Related Maps and Information in Hungary) project is to significantly extend the potential, how demands on spatial soil related information could be satisfied in Hungary. Although a great amount of soil information is available due to former mappings and surveys, there are more and more frequently emerging discrepancies between the available and the expected data. The gaps are planned to be filled with optimized digital soil mapping (DSM) products heavily based on legacy soil data, which still represent a valuable treasure of soil information at the present time. The paper presents three approaches for the application of Hungarian legacy soil data in object oriented digital soil mapping.

We compiled maps for the topsoil (0–30 cm) organic carbon (SOC) stock and its prediction uncertainty in Hungary at 100 m resolution for the years 1992 and 2010 using a machine learning algorithm, namely, quantile regression forest. 10-fold cross-validation was used for checking the accuracy of the spatial predictions and uncertainty quantifications for both years. The performance of the spatial predictions and uncertainty quantifications was appropriate, which was verified by the computed biases (0.15 and 0.30 for 1992 and 2010), root mean square errors (21.99 and 21.39 for 1992 and 2010), accuracy plots and the G statistics (0.96 for both years) as well. Based on the compiled SOC stock maps, we assessed the spatio-temporal change of SOC stocks on the territory of Hungary. A scheme was elaborated based on the quantified prediction uncertainties for identifying and delimiting significant and tendentious changes of SOC stock during the respective period. The total SOC stock in the topsoil was found to be 424.41 Tg (1 teragram = 1012 grams) in 1992 and 451.59 Tg in 2010. Thus SOC stock increased by 27.18 Tg over the respective period. On those areas where the land use types did not change, we observed that the SOC stock increased under forests (by 16.29 Tg) and pastures (by 2.48 Tg), decreased under wetlands (by 0.49 Tg) and did not change under agricultural areas. On those areas where the land use has been changed during the 18-year period, we found that afforestation has increased the SOC stock, whereas cultivation of pastures has decreased it. Due to soil sealing 34,000 ha of soil have been lost resulting in approximately 1.7 Tg carbon loss. We compared our own total SOC stock estimate and map referring to 1992 with other estimates and maps provided by global and continental initiatives. The comparisons have pointed out that the SOC stock map of 1992 outperformed these maps. We recommend applying the SOC stock map of 1992 as a baseline for Hungary.

A talajra vonatkozó térbeli információ igények nem minden esetben elégíthetőek ki csupán a rendelkezésre álló adatok alapján. Közvetlen megfeleltetés híján csak bizonyos konverziók útján juthattunk a kérdéses helyszínekre vonatkozó megfelelő információhoz. Jelen munkánk során talajtani adatainkat egy élőhely-tipizálási kutatás számára alakítottuk át. Az első lépés az adott talaj kategóriák összehangolása a Digitális Kreybig Talajinformációs Rendszerrel (DKTIR). A kidolgozott megfeleltetési sablon szerint a gyakorlati megvalósítást egyrészt a DKTIR talajfolt szintű tulajdonságok területi lekérdezésével, másrészt a talajszelvény adatbázis térbeli kiterjesztésével (indikátor krigelés), majd ezek területi megoszlását számolva végeztük. Adott pontban leginkább valószínűsíthető kategóriát a legnagyobb területi aránnyal előforduló talajokra adtuk meg. Eredményként mintegy 3500 pontra elkészült a leginkább valószínűsíthető kategória (szik, homok, lösz, láp, erdő-, öntés talaj) térkép, amely további kutatás egyik építőköve a kiemelt jelentőségű élőhelyek országos trendelemzésében.

Kategória típusú talajtérképek térbeli felbontásának javítására (leskálázására) adatbányászati módszerként osztályozó fákat alkalmaztunk. A feladat elvégzését az indokolta, hogy bizonyos tematikus talajtérképek nem állnak rendelkezésre a megkívánt léptékben. A számos előnnyel bíró döntési fák felhasználhatók többek között létező talajtérképekben foglalt talaj-táj modellek megértésére, a felvételezési, szerkesztési szabályok utólagos formalizálására. A feltárt, döntési szabályokba foglalt összefüggések pedig nagy felbontású környezeti segédváltozók segítségével térbelileg finomított térképek előállítását teszik lehetővé. Ezen segédváltozók között speciális szerepet töltenek be a nagyobb térbeli felbontású, de eltérő tematikájú talajtani információk. A szintetizáló munka eredményeként született Agrotopográfiai térképek agroökológiai egységei döntően a Kreybig-féle talajfelvételezés adataira alapozva, a Kreybig térképek talajfoltjainak térbeli és tematikus generalizálásával jöttek létre. A Kreybig mintázat jelentős információtartalommal bír ezek heterogenitására vonatkozóan, csakúgy mint a talajképződésben jelentős szerepet betöltő domborzati viszonyokat nagy léptékben jellemző domborzat modellek.Az ország teljes területére elérhető AGROTOPO és DKTIR (Digitális Kreybig Talajinformációs Rendszer) adatbázisok, illetve digitális domborzat modellek révén hatalmas potenciál áll rendelkezésre, mely lehetőségek integrált kiaknázásával számos kategória típusú tematikus talajtérkép leskálázására nyílik lehetőség. Ezek közül kettőt mutattunk be részletesebben: (i) Az Országos Területrendezési Terv Kiváló Termőképességű Területeinek országos léptékű lehatárolásához az AGROTOPO talajértékszám kategória térképét skáláztuk le döntési fák segítségével. (ii) Az öntözés tervezését szolgáló nagyléptékű térképezési módszertan digitális implementálásának feltétele a talajok genetikus osztályozásának ismerete 1:25.000- es léptékben. Egy belvízöblözet területére az AGROTOPO genetikus típus fedvényét skáláztuk le a DKTIR és természetesen egyéb környezeti segédváltozók, illetve osztályozó fák felhasználásával.A felhasznált módszert a későbbiekben is alkalmazni kívánjuk hasonló feladatok megoldására, például az országos digitális talajtérképezési projektben (DOSoReMI.hu; PÁSZTOR et al., 2013b), a levont következtetéseket és a tanulságokat pedig hasznosítani. Továbblépést a környezeti segédadatok körének bővítésével, illetve a döntési fák egy további szintjének, az ún. „random forest” (véletlen erdő) módszercsalád alkalmazásával tervezünk.Munkánkat az K105167 OTKA pályázat és a Bolyai János Kutatási Ösztöndíj program támogatta.