PICO
The aim of this session is to highlight a broad range of research methods and results related to climate change. This interdisciplinary session should reflect, discuss, and share scientific knowledge on a local and regional scale with the aim to increase innovative knowledge on climate change and its impacts, ecosystem response and new techniques to prevent and reduce the negative consequences.
This session encourages contributions from several fields related to:
- climate change impacts (biodiversity loss, rising temperatures, hydrological extremes, soil degradation, ecosystem response to climate change);
- droughts and floods; precipitation deficiency or extreme precipitation with solutions aimed at reducing the negative impacts;
- ecological stability and climate change; changes of ecological stability, deforestation, human interactions with the environment and evaluation of restoration success;
- green cities to increase the ecological stability of the urban landscape;
- techniques and methods to prevent and reduce the negative impacts of climate change (such as soil degradation, carbon sequestration, changes in natural, agricultural, and forest ecosystems, reduction of overall ecological stability and character of the landscape);
In addition, attention will be given to the sustainability of management practices, the importance of appropriate land use management as the main tool for preventing the degradation processes, the distribution and vitality of ecosystems, and improving the condition of forest ecosystems in order to increase the overall character of the landscape.
We conducted this research in Aldammar locality, River Nile State, Sudan. Research aimed to 1) assess tree diversity and composition, 2) examine community perceptions toward the Dom palm. A stratified conventional inventory was used. Regarding climate change, a total of 36, 12, and 11 sample plots (each 0.10 ha, radius 17.8 m) were established in Geli, Elhelgi, and Umbasheem forests, respectively. In each sample plot, we identified all trees to the species level, recorded their frequencies, and computed species diversity and importance value indices (IVI). Socio-economic data were collected using a structured household survey administered to 146 respondents distributed across seven randomly selected villages, complemented by 20 key informant interviews. Data was analyzed using Microsoft Excel and SPSS. The results revealed that 8, 7, and 6 tree species belonging to six families were recorded in three sites. The mean tree density was 254.33 trees/ha, 1611.33 trees/ha, and 337 trees/ha for the respective sites. The dominant species were H. thebaica in Umbasheem, which exhibited richness (R=11), Dominance (D' = 0.55), Simpson’s Diversity (D = 0.45), Shannon Index (H' = 1.12), and Evenness (E 0.47). Additionally, Prosopis spp. is dominant in Elhelgi and Geli sites as well. The study noted present (59) individuals of the Dom regeneration in Umbashem and absent in the others. H. thebiaca. Regarding community perceptions, respondents indicated that the status of the Doum palm stands is degraded, and that the invasive Prosopis spp. exerts major negative impacts on Doum forests. The study concludes that the massive expansion of invasive Prosopis spp. is most likely to lead to the degradation and potential destruction of Dom palm (H. thebaica) resources, especially under the current management practices, and observed a significant absence of Dom regeneration. the study recommended adopting new approaches and prospective to Dom palm management.
How to cite: Abdelkarim, H., Horváth, A., and Mohamed Dafa-Alla, D.-A.: Impact of Invasive Species and Tree Diversity on the Dom palm: Community Perception and Human-Induced Changes, Dryland, Sudan, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1144, https://doi.org/10.5194/egusphere-egu26-1144, 2026.
Alien tree species are key to improving and enhancing the sustainability of urban green spaces and forest management, but they also pose a threat to global biodiversity in the context of climate change and urbanisation. Using data on the occurrence of the alien tree species Acer negundo L. from the Gbif database, we modelled the availability of potential ecological niches using the MaxEnt method, 19 bioclimatic variables and two additional variables (altitude as an indicator of distribution dependence on relief, human population density) for current conditions, the periods 2041–2060 and 2081–2100 for the territory of Europe. We used two climate scenarios: ssp 126 and ssp 585. We assessed the risks of range expansion for 51 European countries and provided a red list of countries most at risk of invasion by 2100.
Acer negundo is widespread in 31 European countries, with the highest infestation rates in Estonia, Latvia, Slovenia, Serbia, Belarus, the Åland Islands, Romania, Denmark, Georgia, Bosnia and Herzegovina, Bulgaria, Sweden, and France. The Czech Republic and Slovakia have a 16% spread of ssp 585 (2081–2100).
All other countries out of 31 have a forecast of 1-10% of their territory being infected by 2100. In Estonia, Latvia, Slovenia, Serbia, and Belarus, the predicted invasion is 14-75% of the territory in all scenarios and analysed periods, with the most significant expansion of the range in the 15 countries mentioned occurring according to the ssp_126 (2081–100), in which climate change is significantly milder than in ssp_585. Thus, the assessment of invasion risks under the projected climate change scenarios showed that 15 countries have a high risk of invasion. Two countries (Estonia and Latvia) have a 40-75% risk of invasion, with the most significant spread predicted in both scenarios by 2060.
In the Netherlands, Norway, Moldova, Montenegro, Liechtenstein, Andorra, Armenia, Vatican City, the United Kingdom, Greece, Spain, and San Marino, there will be virtually no spread of the species.
How to cite: Miroshnyk, N.: Assessing the potential risk of spreading the invasive tree species Acer negundo L. with climate change in Europe, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-876, https://doi.org/10.5194/egusphere-egu26-876, 2026.
Soil erosion continues to pose a major global challenge, yet long-term catchment-scale analyses that explicitly connect historical land-use change with erosion responses remain scarce. This study examines the influence of approximately +240 years of historical and projected land-use change on soil erosion in the Myjava Basin by incorporating parcel-level land-use reconstructions spanning 1787–2030 into a distributed USLE-2D modelling framework. The R, K, and parcel-based C and P factors were temporally harmonized, while the LS factor was derived using an ensemble of four widely used algorithms. Principal component analysis was employed to assess the relative contribution of RUSLE factors through time, and all analyses were conducted within a reproducible geospatial modelling workflow. The results reveal a long-term reduction in total soil erosion of approximately 78% at the landscape scale and 60% within arable land from the nineteenth century to the present, primarily driven by a substantial decrease in arable land cover from 62% to 37% and the expansion of forest and shrub vegetation. Despite this overall decline, persistent erosion hotspots remain concentrated on steep upland slopes with high LS values (>10%), while agricultural parcels consistently exhibit erosion rates 10–20 times higher than the basin-wide mean across all periods. The PCA indicates that LS and rainfall erosivity are the dominant controls on erosion variability, with principal component loadings ranging from 0.78 to 0.84, whereas the influence of C and P factors increases in recent and projected periods, accounting for up to 40% of the total explained variance. Overall, these results demonstrate that long-term land-use transitions have markedly reduced basin-scale soil erosion risk.
Acknowledgments: This work was supported by the Slovak Research and Development Agency under contract no. APVV 23-0332, VV-MVP-24-0208 and VEGA Grant Agency no. 1/0657/25. The authors are grateful for the support.
How to cite: Putra, A. N., Výleta, R., Danáčová, M., Hlavčová, K., and Kohnová, S.: Catchment-Scale Soil Erosion Response to Long-Term Land Use Change in the Myjava Basin, Slovakia, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4825, https://doi.org/10.5194/egusphere-egu26-4825, 2026.
Water availability and quality is essential for natural ecosystems and sustainable societies, due to its central position in all living and natural interactions, which is ultimately linked to the socio-economic-ecological health of a region. Water and forests are intertwined as their interactions along with climatic, topographical, ecological and edaphic factors play an essential part in water regulation between land and atmosphere. Rising deforestation and degradation have diminished the climate and water regulatory functions of forests threatening the water quality and quantity in forested watersheds. Given the growing global concerns over water security and climate change, understanding these interlinkages have become imperative for sustainable water management. Therefore, exploring water dynamics in conjunction with vegetation and climatic indicators is crucial for a comprehensive assessment of the forest-water-climate nexus. Forest-fed streams and rivers predominantly spanning the southern and central parts of India are dependent on the rainfall and groundwater flows but changing climate and forest patterns have negative connotations for perennial water flows. The largest west-flowing Central Indian River, the Narmada has high ecological, economic, social, religious, cultural importance and dependence. With more than 30% of the basin being forested, the basin comprises 150 watersheds in different agro-ecological zones with varied climatology and hydrology. Other dominant land use is agriculture covering almost 57% of the basin, closely tied to the economy of 17,493 villages and the livelihood of residents. This necessitates a deeper understanding of long-term patterns of eco-hydro-meteorological variables in differently forested watersheds for planning holistic forest-water-climate adaptation and management strategies. Therefore, varying trends in stream discharge, climate and vegetation were assessed for two distinctly forested watersheds of Narmada River. This study examines the forest-water linkages and the changing climate patterns of Dindori (Tropical Moist Deciduous-Sal dominant) and Barwani (Tropical Dry Deciduous-Teak dominant) watersheds with different forest types and cover. Long-term trend analysis (2001-2020) was conducted at annual, monthly and seasonal time scale for selected climate, forest, soil and water variables through appropriate indicators (minimum and maximum temperature, rainfall, evapotranspiration, Normalized Difference Vegetation Index, Enhanced Vegetation Index, Modified Soil Adjusted Vegetation Index, forest cover, soil moisture, and water discharge). The study followed an integrated approach combining station data supplemented by remotely sensed proxy indicators, secondary literature and trend analysis using Mann-Kendall statistical test. The results indicate shifting rainfall patterns, increasing minimum and maximum temperature with expanding agriculture area and reduction in forest cover in both watersheds. Declining patterns of stream discharge, increased drought frequency and evapotranspiration losses were also observed. These findings reiterate the need for integrated forest-water management for a climate resilient future of the Narmada basin. A comprehensive perspective for water variations should involve associated parameters which can inform integrated water management for developing countries like India.
How to cite: Singh, M., Srikar, R., Sinha, B., Bisaria, J., and Thomas, T.: Deciphering the Water-Forest-Climate nexus through long-term hydro-climatic trends in watersheds of Narmada River, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1239, https://doi.org/10.5194/egusphere-egu26-1239, 2026.
Urban areas in Central Europe face rapidly increasing risks from extreme heat and drought, with cascading impacts on health, critical services, and peri-urban food production. Within the TRACAP project, we develop a municipal-scale climate-risk evidence base for Trnava (Slovakia) by combining regional climate projections with local observations and spatial layers describing exposure and vulnerability. Heat hazard is characterised using scenario-based indicators of hot conditions (frequency and severity of hot days/heatwave episodes) and complemented by remote-sensing land-surface temperature to identify persistent urban hot spots and overheating risk for sensitive facilities and populations. Agricultural drought risk is assessed using climate-driven indicators describing water-stress conditions relevant to crop production (precipitation deficit, atmospheric evaporative demand, and drought persistence), and linked to local land use and crop distributions to quantify potential impacts on yields and revenue. Risk is derived by overlaying heat and drought hazards with exposure (critical services, vulnerable buildings, transport assets, and agricultural areas) and vulnerability proxies, producing prioritised hotspots and decision-ready metrics for adaptation planning. The approach demonstrates how workflow-based risk assessment can be operationalised for cities with limited internal capacity, enabling transparent prioritisation of cooling strategies, nature-based solutions, water-retention measures, and drought-resilient agricultural practices.
How to cite: Kubáň, M., Choleva, M., Kohnová, S., Výleta, R., and Štefunková, Z.: Regionalised urban climate-risk mapping for Trnava (Slovakia): integrating Euro-CORDEX-scale projections with local evidence (TRACAP), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4859, https://doi.org/10.5194/egusphere-egu26-4859, 2026.
Long-distance relationships between climate phenomena, known as teleconnections, provide a useful framework for linking pressure anomalies over the North Atlantic and the Arctic to regional variability of hydroclimatic series. Among these, the North Atlantic Oscillation (NAO) and the Arctic Oscillation (AO) are widely recognized as dominant modes influencing winter climate in Europe, yet their impacts on hydrological variables are known to be temporally non-stationary. We examined the influence of the NAO and AO on the intra-annual variability of monthly specific runoff, snow depth, precipitation, and air temperature. The analysis draws on long-term observations from 26 small to medium-sized catchments spanning the western Carpathians and the adjacent Pannonian Plain, covering a wide range of hydroclimatic and physiographic conditions.
To capture scale-dependent relationships, the Continuous Wavelet Transform (CWT) with a Morlet basis was applied to the hydroclimatic time series and the AO/NAO indices. Wavelet coherence was used to identify statistically significant time-frequency regions of co-variability, which are subsequently employed as spectral filters to reconstruct the oscillation-related components of the hydroclimatic signals. The relative contribution of each climate mode is quantified using a signal-to-noise ratio (SNR), defined as the ratio b between the variance of the coherent, climate-related component and the residual background variability.
The results reveal pronounced temporal intermittency in the influence of both NAO and AO, with the strongest impacts occurring during winter and spring high-flow periods. The NAO generally exhibits a stronger and more spatially coherent imprint, particularly during winter and early spring, whereas the AO contribution is weaker and more episodic. The identified non-stationary fingerprints of NAO and AO highlight the scale-dependent and time-varying nature of teleconnection controls on runoff generation and snow accumulation and may have direct implications for runoff predictability, water-resources management, and the interpretation of long-term hydroclimatic variability in Central Europe under a changing climate.
Acknowledgements
This work was supported by the Slovak Research and Development Agency, under the contract No. APVV-23-0332; VV-MVP-24-0208, and the VEGA grant agency under contract No. VEGA 2/0115/25, VEGA 1/0657/25.
How to cite: Výleta, R., Onderka, M., Kohnová, S., and Szolgay, J.: Tracing the Effects of NAO and AO Signals on Specific Runoff, Snow Depth, Precipitation and Air Temperature in the western Carpathians, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5237, https://doi.org/10.5194/egusphere-egu26-5237, 2026.
Accurate representation of river channel geometry is a key prerequisite for reliable hydraulic and aquatic habitat modelling. Traditionally, detailed field surveys combining topographic and bathymetric measurements have been used for this purpose. However, such data are time-consuming, costly, and logistically demanding, and are often unavailable for long-term or spatially extensive applications. An alternative is publicly available airborne laser scanning (LiDAR) data, which provide topographic information with high spatial resolution and full areal coverage, but do not directly capture the submerged morphology of the river channel.
Minimum flows represent critical hydrological conditions during which aquatic habitat availability and quality are strongly constrained by channel hydraulic and morphological controls. Under low-flow conditions, the spatial distribution of aquatic biota is primarily governed by water depth and flow velocity, together with the availability of morphological refugia that enable organism persistence during hydrological stress. Inadequate representation of the channel bed may therefore result in distorted hydraulic conditions and, consequently, in unreliable assessments of aquatic habitat suitability.
For this reason, the present study compares river channel geometry derived from detailed field surveys with geometry based on publicly available LiDAR-derived topographic data, with the aim of quantifying geometric distortions arising from the omission of bathymetry and evaluating their potential effects on aquatic habitat modelling under minimum-flow conditions.
The analysis was conducted on a selected reach of the Nitrica River in Slovakia, representing a small sub-mountain stream with pronounced morphological variability. Two sets of geometric inputs were compared: (i) reference geometry derived from a detailed topographic and bathymetric field survey conducted in 2019, and (ii) geometry based on LiDAR-derived topographic data from the national digital terrain model (DTM 5.0, spatial resolution 1 m, updated in 2025).
The results indicate that, for small mountain and sub-mountain streams, the exclusive use of LiDAR-based topographic data leads to substantial underestimation of flow depth and distorted representation of key habitat features. Consequently, LiDAR data cannot replace detailed bathymetric surveys for accurate aquatic habitat assessment under minimum-flow conditions, when habitat quality is primarily determined by riverbed morphology.
However, the question remains open as to the channel width and flow conditions at which water depth ceases to be the dominant factor influencing habitat suitability, even within mountain and sub-mountain streams. Identifying this threshold represents an important direction for future research, which would allow refinement of methodological guidelines regarding the applicability and limitations of publicly available LiDAR data for aquatic habitat assessment under varying hydromorphological conditions.
Acknowledgement:
This work was supported by the Slovak Research and Development Agency, under the contract No. VV-MVP-24-0208 and the VEGA grant agency under contract No. VEGA 1/0067/23.
How to cite: Štefunková, Z. and Ivan, P.: Limitations of LiDAR Data for Aquatic Habitat Modelling under Low-Flow Conditions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6907, https://doi.org/10.5194/egusphere-egu26-6907, 2026.
The European Space Agency’s Sentinel-1 mission provides observations at spatial resolutions of up to 10 m, making it more relevant not only for continental but also for regional hydrological applications. While previous studies have shown that remotely sensed soil moisture can improve runoff simulations in lowlands, the use of satellite-derived soil moisture products in mountainous environments remains limited due to challenging topography, varying climate conditions, and the lack of reference measurements. This study presents in situ soil moisture measurements collected in the Western Tatra Mountains and their comparison with a newly developed Sentinel-1 surface soil moisture product. The study was conducted in the Jalovecký Creek catchment (Western Tatras, Slovakia), which represents the typical hydrological conditions of the headwater catchments in the highest part of the Carpathian Mountains. Field campaigns were carried out at multiple open and forested sites, focusing on elevation gradients, land cover types, and aspect under different wetness conditions to capture soil moisture variability. Results from the field measurements and the validation of the satellite-derived soil moisture product will be presented.
This work was supported by the Slovak Research and Development Agency under Contracts No. APVV-23-0332 and VV-MVP-24-0208, the VEGA Grant Agency No. 2/0019/23, and the Danube Region Programme: DRP0200156 Danube Water Balance. The financial support by the Action Austria - Slovakia, Cooperation in Science and Education (project No. 2025-03-15-005) is also gratefully acknowledged.
How to cite: Sleziak, P., Massart, S., VillegasLituma, C., Danko, M., Jančo, M., Parajka, J., Vreugdenhil, M., Tanhapour, M., and Dvorak, M.-T.: Validation of a Sentinel-1 soil moisture product in a mountain catchment, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8140, https://doi.org/10.5194/egusphere-egu26-8140, 2026.
Local meteorological measurements are essential because they provide accurate information for regions with unique climatic and geographical characteristics. In this study, data from Sopron’s Botanical Garden and Hermes meteorological stations were digitized and quality controlled. Due to its location, the Hermes station offers valuable insight into sub-montane forest climate conditions, while the Botanical Garden represents a peri-urban, forested park microclimate. Based on data availability, different periods were compared (Botanical Garden: 1930–1960, 1989–2019; Hermes: 2014–2023) with Sopron’s official reference station (Kuruc hill) using basic statistical methods, including time-series analysis and precipitation frequency analysis. In addition, SPI (Standardized Precipitation Index) applied to the datasets.
The results indicate microclimatic differences among the stations. Hermes proved to be the coolest and wettest site, with a higher frequency and magnitude of daily precipitation events compared to the urban park station. Over the past 30 years (1989–2019), mean air temperature increased significantly relative to the reference period of 1930–1960 The SPI analyses of the Botanical and Kuruc Hill show a very high similarity, but the Botanical Garden has less extreme negative (drought-related) values. There are larger differences between the Kuruc Hill and Hermes SPI. Hermes SPI shows a more stable, drought-resistant picture, with fewer negative values than the Kuruc Hill, which has a drying tendency. SPI analysis reveals that urban environments experience more frequent and persistent drought conditions than forested areas. These datasets effectively capture micro- and mesoclimatic trends in the Sopron region and can provide a robust basis for validating climate models or other climate related analyses.
This research was supported by the Hungarian Ministry of Agriculture. This study was financially supported by the Slovak Research and Development Agency under Contract No. APVV 23-0332 and VEGA Grant under Contact No. 1/0577/23. This study was financially supported by The Programme for Motivation and Support for Increasing the Quality and Efficiency of Scientific Research Activities of Young Researchers, Contract No. 1636.The research was supported by the OTKA grant 143972SNN, the Slovenian Research and Innovation Agency grant N2-0313 and the associated project TKP2021-NKTA-43. The project TKP2021-NKTA-43 was implemented with the support of the Ministry of Innovation and Technology through the National Fund for Research Development and Innovation, funded by the TKP2021-NKTA call for proposals.
How to cite: Megyer-Muraközy, L., Kalicz, P., Gribovszki, Z., Hlavčová, K., and Szolgay, J. S.: Micro- and mesoclimatic trends in Sopron region, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9466, https://doi.org/10.5194/egusphere-egu26-9466, 2026.
Climate change impact assessments frequently rely on synthetic or downscaled meteorological datasets that may lack essential climatic variables such as humidity, radiation, and wind speed. This deficiency restricts the applicability of classical reference evapotranspiration (ETo) models, particularly the FAO-56 Penman-Monteith approach, which requires multiple climatic inputs and thus introduces additional uncertainty. This study aims to develop a data-efficient methodology for estimating ETo and irrigation water requirements using only temperature and precipitation, variables that are more readily available and less uncertain in climate generators. Two modelling approaches for ETo are evaluated: machine learning and optimised empirical equations. Machine learning models were trained on CarpatClim database. Although this database only contains data up to 2010, the authors of the study show the advantages of using such products for training models that can be used for future periods and for prospective studies of the impact of climate change. Daily ground-based meteorological records from the case study region also support calibration and validation. Model performance is assessed using a range of statistical measures.
Results indicate that machine learning models can accurately estimate ETo with minimal input data, outperforming empirical equations in both accuracy and predictive robustness. The estimated ETo values are incorporated into a water balance framework to determine irrigation water abstractions, accounting for soil moisture conditions, precipitation deficits, and plant water demand. For this purpose, a custom model based on the FAO CROPWAT model was created in the R language. These findings demonstrate the potential of a hybrid machine learning and water balance approach for assessing evapotranspiration and irrigation requirements under limited data conditions.
The proposed methodology offers significant benefits for climate change impact studies, agricultural water planning, and regions with incomplete meteorological observations. It also advances the practical implementation of data-light irrigation modelling, supporting broader applications in hydrological and environmental management.
ACKNOWLEDGEMENTS
The author thanks the VEGA Grant Agency for funding projects VEGA 1/0067/23 and 1/0724/26, within the context of which this research was accomplished.
Keywords: reference evapotranspiration, machine learning, CarpatClim database
How to cite: Cisty, M.: Robust Evapotranspiration Estimation Under Limited Data Conditions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17774, https://doi.org/10.5194/egusphere-egu26-17774, 2026.
Urban areas are increasingly exposed to compound hydrometeorological extremes, particularly combinations of heat waves and moisture anomalies, which strongly affect vegetation vitality and urban microclimate. Urban green infrastructure represents a key adaptation measure; however, its performance under compound stress conditions requires systematic evaluation at the local scale.
This study assesses the response of urban vegetation and surface thermal patterns to compound heat-related stress in selected public spaces within the city of Trnava (Slovakia) using satellite-derived indicators. Multispectral satellite imagery from Sentinel-2 and Landsat missions was used to derive the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST), serving as proxies for vegetation condition and surface heat load. The data were subjected to spatially explicit processing and comparative analysis to identify patterns of vegetation vitality and cooling effects across different urban surface types.
The analysis focuses on periods characterized by elevated temperatures combined with limited moisture availability, representing typical compound stress conditions in urban environments. The results reveal pronounced spatial variability in vegetation resilience and cooling efficiency, highlighting the importance of vegetation structure, coverage, and spatial configuration in mitigating urban heat. The findings demonstrate the applicability of satellite-based approaches for evaluating nature-based solutions and provide practical implications for urban climate adaptation, green infrastructure planning, and the design of climate-resilient public spaces in medium-sized cities.
Acknowledgements
This work was supported by the Slovak Research and Development Agency, under the contract No. APVV-23-0332; VV-MVP-24-0208, and the VEGA grant agency under contract No. VEGA 1/0577/23 and VEGA 2/0115/25 and Programme for Motivation and Support for Increasing the Quality and Efficiency of Scientific Research Activities of Young Scientific Researchers (project name: COMPLANT)
How to cite: Bohumelová, L. and Výleta, R.: Satellite-Based Assessment of Urban Green Infrastructure under Compound Heat Stress in the City of Trnava, Slovakia, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9546, https://doi.org/10.5194/egusphere-egu26-9546, 2026.
Due to the changing climate, there has been a growing interest in solutions to reduce the carbon dioxide content of the atmosphere in recent decades. The utilization of the natural potential and the applied land uses in a given area directly affect the sequestration of carbon dioxide from the atmosphere. Within the framework of our research, we aim to estimate the carbon sequestration and carbon storage capacity of the Austrian-Hungarian border region based on land use.
We utilized the land cover categories of the CORINE database, which is available for a significant portion of Europe. Based on the literature sources and our own measurement results for the border region, we assigned potential carbon storage values to the land cover categories, which allows us to estimate the amount of stored carbon for the entire region. In addition to determining the current carbon storage capacity value, the database also allows us to track past changes in the region's carbon storage using the CORINE land cover maps, which are updated every six years.
The research was carried out within the framework of the CS4Region project, identification number ATHU-0100046, with the support of the INTERREG AT-HU 2021-2027 program.
How to cite: Balázs, P., Horváth, A., Polgár, A., and Bidló, A.: Carbon stock of the Austrian-Hungarian border region, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16745, https://doi.org/10.5194/egusphere-egu26-16745, 2026.
How to cite: Bidló, A., Balázs, P., Végh, P., and Horváth, A.: Organic carbon stocks in the soils of western Hungarian forests, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16844, https://doi.org/10.5194/egusphere-egu26-16844, 2026.
How to cite: Horváth, A., Balázs, P., Felvidéki, P., and Bidló, A.: Combating climate change through the use of biochar - Preliminary results on the effects of biochar application on different forest soils, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18660, https://doi.org/10.5194/egusphere-egu26-18660, 2026.
Slovakia, like many other countries, has experienced an increase in extreme weather conditions caused by climate change. At the beginning of September 2024, following an extremely warm and dry period, a significant shift to cold autumn weather occurred, particularly in western Slovakia, accompanied by heavy precipitation and strong winds. According to forecasts, continuous heavy rainfall was expected over five days, which was expected to alleviate the dry conditions across the entire region. The rainfall was also anticipated to cause a significant rise in water levels, potentially reaching flood stages and increasing the risk of flooding.
The discharge rates of surface water during the summer months reached very low values. In some cases, they were close to reaching absolute minima at water gauging stations. August was evaluated as the driest month in 2024, after the aforementioned extraordinary precipitation totals on 11.9. – 16.9.2024, with a recurrence period of up to 200 years, there was a significant change in the hydrological situation, especially in the Slovak part of the Morava and Danube River basins. Significant increases in the water levels were recorded. During this time, 64 direct discharge measurements were carried out on fourteen rivers in the Morava River basin, and another 34 direct measurements on 4 rivers in the Danube River basin. To assess the impact of the extreme situation, the obtained data were analyzed, and the hydrological situation was evaluated.
Keywords: September 2024, floods, Morava River basin, Danube River basin
Acknowledgment: This work was supported by the Slovak Research and Development Agency under the Contract no. APVV-23-0332 and as part of project „Udržitelné hospodaření s podzemními vodami v česko-slovenském příhraničí“, ITMS21+:403201DNJ4, an Interreg Slovensko-Česko 2021-2027 Programme project co-funded by the European Union.
How to cite: Kotrikova, K., Danacova, Z., Boraros, T., Dzurik, D., and Zlatinsky, R.: September 2024 floods in the Slovak part of the Morava and Danube River basins, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19373, https://doi.org/10.5194/egusphere-egu26-19373, 2026.
Climate change is expected to increase the frequency and volume of short-duration, high-intensity rainfall events in many regions. These changes can strongly affect runoff generation processes in hilly catchments, where rapid subsurface flow responses may play a key role during extreme precipitation events. However, direct field-based evidence of near-surface lateral flow (interflow) at the hillslope scale remains limited.
This study presents field-based evidence of near-surface lateral flow in a small forested hillslope catchment in southern Hungary. The investigation combines multi-depth soil moisture monitoring with a plot-scale controlled infiltration experiment to analyse subsurface water movement under intense water input conditions. Volumetric soil water content was measured at depths between 10 and 100 cm using frequency domain reflectometry (FDR) sensors, providing high temporal resolution data during infiltration events. In parallel, an artificial rainfall experiment was carried out on a bordered hillslope plot to enable event-based water balance estimation.
Soil profile observations revealed a vertically heterogeneous soil with a shallow humic layer, an underlying permeable horizon, and a clay-enriched subsoil showing signs of temporary saturation. This vertical structure creates a hydraulic contrast that restricts vertical percolation during intense infiltration. As expected, soil moisture measurements showed rapid wetting in the upper soil layers, while deeper layers responded more slowly. Water balance calculations indicated that a considerable part of the water applied to the surface could not be detected in the change of the vertical soil water storage, suggesting a subsurface lateral flow distribution within the near-surface soil layers.
The timing and depth distribution of soil moisture responses, together with the water balance results, provide consistent evidence for the activation of near-surface lateral flow along soil horizon boundaries with contrasting hydraulic properties. The findings highlight the importance of subsurface flow processes in forested hillslope hydrology and underline the need to consider near-surface lateral flow when assessing runoff generation under increasingly extreme rainfall conditions.
How to cite: Koch, D., Majer, F. K., Pap, M., Tamás, E. A., Keve, G., Ámon, G., and Illés, Z.: Field-based identification of near-surface lateral flow in a forested hillslope catchment, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20985, https://doi.org/10.5194/egusphere-egu26-20985, 2026.
With the Agreement on the Conservation and Sustainable Use of Marine Biological Diversity of Areas beyond National Jurisdiction (BBNJ Agreement) entering into force on January 17, 2026, the governance landscape for the global ocean has fundamentally shifted. However, current Integrated Assessment Models remain largely “dematerialized,” effectively modeling the carbon mitigation but failing to account for the plastic cycle—an anthropogenic flux that explicitly threatens the “carbon cycling services” the BBNJ Agreement is now legally mandated to protect. Consequently, current scenarios could underestimate the complex chemical reactions resulted by the production, accumulation, and degradation of synthetic polymers.
We propose an AI-Enhanced Material Flow Analysis (AI-MFA). Rather than building a computationally expensive process-based module from scratch, we leverage Ensemble Machine Learning (specifically Random Forest and Gradient Boosting Regressors)—methods identified as robust and accessible in the state-of-the-art sustainability AI literature. Firstly, we train the ML ensemble on historical industrial ecology datasets (OECD Global Plastics Outlook, World Bank “What a Waste 2.0”) to learn the non-linear correlations between socio-economic drivers (GDP, urbanization, industrial structure) and plastic flows. Secondly, we apply these trained models to the deterministic socio-economic drivers of the Shared Socioeconomic Pathways (SSPs) used in CMIP6 and proposed for CMIP7. This allows us to “project” the plastic reality into the future for scenarios ranging from SSPs to emission-driven pathways in ScenarioMIP-CMIP7. Thirdly, we estimate three critical fluxes: (a) the production material wedge, (b) the accumulated environmental stock, and (c) the degradation impact potential.
We anticipate establishing a “Plastic Intensity Baseline” for current CMIP7 pathways. Preliminary hypothesis testing suggests that regional rivaly scenarios (e.g., SSP3) contain a “material blind spot” equivalent to substantial unmodeled material pollution. By quantifying the “Plastic Biogeochemial Wedge”—the divergence between the baseline and the circular economy. This metric will serve as a proxy for evaluating whether specific climate pathways risk violating the BBNJ Agreement's mandate to maintain ecosystem integrity in areas beyond national jurisdiction.
How to cite: Park, H., Song, C., and Lee, W.-K.: An AI-Driven Quantification of the Plastic Biogeochemical Wedge in CMIP6/CMIP7 Scenario Pathways, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21570, https://doi.org/10.5194/egusphere-egu26-21570, 2026.
