The Danube River Basin, spanning 19 countries and covering 801,000 km², is the most international river basin in the world. This region faces diverse challenges related to water quantity, quality, groundwater management, and biodiversity, all of which are expected to intensify due to climate change. To address these challenges, a holistic and sustainable water management approach is needed—one that integrates environmental, social, and economic dimensions, ensures stakeholder involvement, and aligns with regulatory frameworks.
Building on the Planetary Boundaries framework, the concept of Safe Operating Space (SOS) has emerged in the last decades to assess sustainable resource use within the Earth’s carrying capacity while maintaining human well-being. Within the Horizon Europe SOS-Water project, we are working to define the SOS for water resources in four case study sites across Europe and beyond (Danube, Rhine, Jucar and Mekong basins) using integrated modeling, monitoring, advanced indicators, and an inclusive and iterative participatory approach that actively engages stakeholders to co-define visions, water values, and management options.
The resulting co-created SOS framework will inform the design of sustainable water management pathways that address current and future challenges. It aims to maximize the socio-economic and ecological value of water while promoting resilience and sustainability across the different river basins.
This proposed talk will showcase the application of the SOS framework to the Danube Basin, highlighting its capability to integrate all the different aspects of the water dimension with stakeholder engagement and co-development of management pathways. We will present the preliminary framework co-developed with stakeholders for the Danube Basin and provide insights into the how it can be used to inform sustainable water management practices and address the critical water challenges facing the Danube Basin and other transboundary regions worldwide.
How to cite: Artuso, S., Politti, E., Tramberend, S., Smilovic, M., and Kahil, T.: Developing a Safe Operating Space framework for water resources in the Danube River basin, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5915, https://doi.org/10.5194/egusphere-egu25-5915, 2025.
Beside common pollutants, such as organic material and nutrients, an ever-widening list of chemicals also put pressure on the quality of our rivers, lakes and the health of the prestigious ecosystems living within them. An investigative work to understand the main sources and pollution pathways of these chemicals is an important task ahead of us. A series of large-scale studies have been undertaken with the cooperation of experts from almost all Danube countries to build a hazardous substance inventory in the first step and then to build an emission model based on this inventory. The inventory has been built within the frames of the Danube Hazard mᶾc InterReg project, the model building is currently ongoing within the frames of the Tethys InterReg project. Three chemical groups are investigated by applying the MoRE (“modelling of Regional Emissions”) model for the Danube River Basin (DRB) represented by key elements and compounds: the group of potentially toxic elements is represented by 6 heavy metals and arsenic, industrial chemicals are represented by the two most common per- and polyfluoroalkyl substances (PFAS), PFOS and PFOA, and human pharmaceuticals are represented by a pain killer (diclofenac) and a psychoactive drug (carbamazepine). Each of these substances are ubiquitous in the environment but linked to different sources and pathways. While the source of pharmaceuticals is fairly well known, the estimation method for their emissions is challenging if one needs to reflect regional differences of it or to account for the effects of the type of sewage treatments applied in the treatment plants. Heavy metals are abundant in soils all over the DRB, while the uncertainties of the emissions from operating and abandoned mining facilities are also key to be addressed if hot spots to be identified. The most difficult, however, is the regionalisation of PFAS substances as beside emissions from point sources and urban runoff, they appear in atmospheric deposition all over the basin and in groundwater around known and potential hot-spots, meanwhile the actual emissions from point sources are also much less documented. A key step to upgrade our inventories for the model is that the emission from industrial facilities to air and water are described in detail as far as data from national and international databases, literature or BAT documents is available. Knowledge gap is indicated by the amount of plants with known discharge (162) compared to all the industrial facility in the DRB (6258 facility identified in the Industrial Emission Directive database). For the most uncertain emission sources and pathways, the study aims an order of magnitude estimation for all the potential estimation sources. Hence, for example tile drain pathway has been introduced for chemicals present in soils, despite the lack of sufficient concentration data in effluents. The estimation of groundwater concentration is not only difficult for diffuse sources but also for hot spots, which may be known only by literature information. The latter (literature values) is applied for landfill sites, which are treated as legacy hot spots for PFAS substances and pharmaceuticals.
How to cite: Jolánkai, Z., Kardos, M. K., Dudas, K., Potó, V., and Clement, A.: Building a transboundary hazardous substance emission model for the Danube River Basin. Overview of the key challenges of data availability, data uncertainty, knowledge gaps of substance behaviour, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20798, https://doi.org/10.5194/egusphere-egu25-20798, 2025.
Chemicals are part of our life. Several hundred thousand are used in multiple applications in the European Union (EU) and may ultimately reach water systems. Chemicals are used as pharmaceuticals, personal care products, pesticides/biocides or so-called industrial chemicals. Losses to the environment may occur throughout all stages of the life-cycle of products. Specifically, mobile, persistent and toxic chemicals (PMTs) are considered as major concern for human and environmental health. Exceedances of current environmental quality standards (EQS) are recorded all over Europe. A significant increase in the number of chemicals that need to be considered and a major tightening of EQS is currently under discussion in the EU.
Emission, fate and transport models can help to map the temporal and spatial variability of environmental exposure and support risk assessment for water bodies where monitoring is lacking. They can be used to identify sources and pathways responsible for current exposures and to assess the impact of potential future developments of PMT-exposures in surface water and groundwater. Such scenario assessment may include changes in PMT use, effects of pollution control measures, accidental spills and climate change impacts. TU Wien led and still leads various research projects for the enhancement of monitoring, modelling and management of PMTs in the Danube Basin: (i) Danube Hazard m3c (EU Interreg Danube Transnational Program) (ii) the “Danube case study” in the frame of the project PROMISCES (EU Horizon 2020) and (iii) Tethys (EU Interreg Danube Region).
This contribution provides a short overview on basic considerations, concepts and methods of these activities and exemplifies them on the case of water pollution with per- and polyfluoroalkyl substances (PFAS) in the upper Danube Basin. Investigations show that an upstream located chemical park and diffuse inputs from urban areas are the main sources of perfluorinated carboxylic acids (PFCA) for surface waters. For perfluorinated sulfonic acids (PFSA), diffuse urban inputs predominate. A large part of the overall emissions is due to legacy pollution, which will persist even if strict source control for PFAS is implemented. Wastewater treatment effluents contribute a share of up to 25% of emissions for both PFAS groups.
Most of the surface waters in the upper Danube River Basin, including the Danube itself, show a low risk of exceeding the threshold of the EU drinking water directive of 100 ng/l for the sum of 20 PFAS. This is of relevance in case that surface waters are used as drinking water source via bank filtration. There is nevertheless a high risk of exceeding the European Commission’s proposed quality standard for surface and groundwater of 4.4 ng l-1 PFOA toxicity equivalents as a sum of 24 PFAS in the Danube and in most of its tributaries. Simulated scenarios show that these risks may be reduced by massive efforts to implement water pollution control measures (including groundwater remediation in hot spot areas). However, the risk might even increase if low effort is made to control water pollution and at the same time the Danube’s flow decreases due to climate change.
How to cite: Zessner, M., Liu, M., Kittlaus, S., and Zoboli, O.: Monitoring, modelling and management of persistent, mobile and toxic chemicals in the Danube River Basin, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5883, https://doi.org/10.5194/egusphere-egu25-5883, 2025.
The Danube Water Balance project launched in 2024 in the frame of the Interreg Danube Region Programme with the aim to i) develop a harmonized hydrological modeling system enabling the analysis of present and future water balance of the Danube basin and to ii) improve data management among Danube countries for present and future water balance calculations. The latter is partially based on the establishment of a data repository for input data of the model. Besides global and regional open access data (e.g. digital elevation model, climate variables), national data are collected in order to i) provide direct input for the model, ii) validate global/regional data and iii) allow for the calibration and validation of the model. Thematically, the data cover environmental, hydrologic and water management, and socioeconomic information. Here, we present the procedure and the results of the collection of national data, starting from the identification of data types, desired quality and relevant resolution through the statistics of collected data to the outcomes of a preliminary data gap assessment. Spatial and temporal data coverage patterns by countries/regions are evaluated, taking into account the differences in environmental conditions and water management specificities. We also present the future steps planned in the project towards a harmonized basin-wide database.
This work/paper was supported as part of DANUBE WATER BALANCE, an Interreg Danube Region Programme project co-funded by the European Union.
How to cite: Kozma, Z. and the Danube Water Balance project data collection team: Establishment of a data repository for hydrological and related data to support water balance modeling in the Danube basin, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17084, https://doi.org/10.5194/egusphere-egu25-17084, 2025.
Understanding groundwater dynamics is crucial for assessing groundwater resilience and supporting water management, particularly in transboundary areas where shared aquifers are often evaluated only at a national level, overlooking the broader aquifer system and data from neighboring countries. Groundwater resilience—the ability of groundwater systems to recover from disturbances such as droughts—is a spatially variable trait influenced by a range of spatial-temporal factors that do not obey borders. This study investigates the spatial and hydrodynamic controls on groundwater dynamics within the Baltic region, focusing on the challenges posed by data discrepancies and monitoring network inconsistencies across Latvia, Lithuania, and Estonia.
We utilized groundwater timeseries indices and the groundwater memory effect to investigate dominant patterns and their correlations with physiographic and climatic controls. Machine learning algorithms were used to explore spatial patterns with similar hydrodynamic characteristics. The analysis of national groundwater level data revealed monitoring gaps, particularly in transboundary aquifers, along with different national approaches in groundwater monitoring networks. These challenges complicate the comprehensive assessment of groundwater dynamics at a regional scale.
The results reveal that topographic, climatic and hydrological features are the most significant drivers of groundwater dynamics, followed by geological features. Groundwater indices and trends highlighted not only natural variability but also anthropogenic impacts on aquifer systems near large cities (e.g. Riga) and mining sites (e.g. Kohtla-Järve). We identify regions lacking monitoring wells and propose potential locations for new groundwater wells based on physiographic and hydrodynamic characteristics.
This research is supported by the GRANDE-U “Groundwater Resilience Assessment through Integrated Data Exploration for Ukraine” (No. 2409395) project.
How to cite: Bikše, J., Haaf, E., and Retike, I.: Groundwater dynamics across borders: data and monitoring network challenges in the Baltic countries, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16367, https://doi.org/10.5194/egusphere-egu25-16367, 2025.
Groundwater is a critical resource that supports ecosystems, agriculture, and drinking water supply, yet its sustainable management faces challenges, particularly in the transboundary regions. Collaborative approaches are needed to protect this shared resource, as pollution or overexploitation in one country can have significant consequences across borders. The Estonian-Latvian transboundary area is a good example of these challenges, with its reliance on both unconfined Quaternary aquifers, essential for ecosystems and rural communities, and confined first bedrock aquifers, critical for centralized water systems.
This study develops a transboundary aquifer vulnerability assessment framework, integrating harmonized methodologies to evaluate natural vulnerability and pollution risk. The analysis uses the DRASTIC and modified DRASTIC index-based methods, combined with the DRASTIC-L approach, which incorporates land use data for a comprehensive evaluation of both natural and anthropogenic pressures. To improve the reliability of the assessment, pollutant travel time calculations were used to validate the findings.
The results show high variability in aquifer vulnerability across the study area. The unconfined Quaternary aquifer is most vulnerable in regions with sandy sediments, shallow groundwater tables, and high recharge rates. The confined bedrock aquifers are covered with protective sediment layers, but their vulnerability varies depending on sediment thickness and hydraulic conductivity. Notably, discrepancies between Estonian and Latvian geological data were uncovered, as large polygons of well-protected areas often terminate abruptly at the border, highlighting inconsistencies in geological data between Estonia and Latvia.
This framework emphasizes the importance of integrating natural vulnerability maps, pollution risk assessments, and harmonized methodologies developed for regional geological conditions. The study offers a scalable and adaptable solution for transboundary aquifer management by addressing data inconsistencies and fostering international cooperation.
Integrating these insights into transboundary water management strategies can greatly improve decision-making by providing a more comprehensive understanding of groundwater vulnerability and pollution risks. Additionally, it helps to make groundwater systems more resilient to future challenges like climate change, land use changes, and increasing water demand. Ultimately, this approach supports the sustainable use and protection of shared groundwater resources, ensuring their availability and quality for current and future generations.
How to cite: Männik, M., Bikše, J., and Karro, E.: Advancing harmonized groundwater vulnerability assessments for sustainable management in the Estonian-Latvian transboundary aquifers, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10445, https://doi.org/10.5194/egusphere-egu25-10445, 2025.
The study assesses dynamics of transboundary water cooperation in the Mekong River Basin focusing on relationships between China and the Lower Mekong countries, namely, Myanmar, Thailand, Laos, Cambodia, and Vietnam. Water diplomacy is deployed as an analytical framework to investigate the extent to which China's Lancang Mekong Cooperation (LMC) since 2015 has carved out a new geopolitical, economic, and environmental landscape. The LMC has become influential and competes with other cooperation mechanisms, such as the Mekong River Commission. China has shared more hydrological data and information and releases emergency water downstream for addressing droughts. These do not demonstrate China's shift toward cooperation but could be regarded as China's 'dressing up domination as cooperation'.
How to cite: Lee, S. and Shin, N.: The Emergnece of the Lancang Mekong Cooperation and its Impacts on the Mekong River Basin, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-96, https://doi.org/10.5194/egusphere-egu25-96, 2025.
Despite the progress in Polish-Ukrainian cooperation on transboundary waters through the establishment of joint regulatory bodies and legislative agreements, the problem of integrated groundwater monitoring still remains unresolved. This study presents the application of remote sensing to address data gaps concerning transboundary groundwater resources. The main advantage of remote sensing measurements is that the data they provide are temporally consistent and include spatial information, unlike point-based in-situ observations. Moreover, due to the use of multiple sensors, remote sensing enables comprehensive studies over large areas simultaneously, which is typically challenging in inaccessible regions.
Currently, only the GRACE/GRACE-FO mission (Gravity Recovery and Climate Experiment and GRACE Follow-On) provides direct measurements of terrestrial water storage (TWS) changes, which are largely governed by groundwater storage capacity. Our study presents the quantification of groundwater resources in terms of fluctuations in the shallow unconfined water table by integrating GRACE/GRACE-FO gravity data, precipitation observations, evapotranspiration, river runoff, and groundwater depth. Using machine learning algorithms, data from multiple sources were assimilated, achieving accurate groundwater quantification at a spatial resolution of 0.1°. Previous assessments of transboundary groundwater resources in the Bug River basin were based on a sparse and uneven observational network with a density of 0.003 points/km², as well as old (often from the 1980s) hydrogeological maps at a scale of 1:50,000.
The results of our novel approach indicate that groundwater resources in the study area are depleting, primarily due to increased evapotranspiration, despite a stable precipitation level of around 700 mm/year. According to GRACE/GRACE-FO observations, between 2012 and 2023, TWS in the Bug River basin decreased at a rate of 8.8±5.2 mm/year. Our comprehensive study serves as a source for the reassessment of available groundwater resources, providing information on the sustainable allocation of transboundary groundwater resources between Poland, Ukraine, and Belarus.
The study was conducted as part of the project GRANDE-U “Groundwater Resilience Assessment through iNtegrated Data Exploration for Ukraine” (NSF Awards No. 2409395 and 2409396).
How to cite: Solovey, T.: Remote sensing’s role in improving transboundary groundwater monitoring and sustainable management: The Bug Basin, Polish-Ukrainian-Belarusian Borderland, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1338, https://doi.org/10.5194/egusphere-egu25-1338, 2025.
The St. Mary and Milk River (SMM) basin is an international transboundary watershed flowing between Canada and the United States. The basin is composed of 2 distinct headwater basins that flow into the Saskatchewan Nelson and Mississippi basin, respectively. A diversion constructed in 1909 conveys water from the higher-yielding St. Mary River into the lower-yielding Milk River. The 1909 Boundary Waters Treaty between the USA and Canada allowed for specific entitlements for each country, allowing for sharing of the combined basin resource between both countries. Lack of storage, conveyance and changing hydrological conditions in the basin have resulted in both countries receiving less than the treaty entitlement, prompting the International Joint Commission (IJC) to study the situation. This research addresses an important part of the IJC study which required implementing hydrological models to simulate natural flow in the SMM basin and understand the reliability of any solution under future climate. The HYPE hydrological model with the HDS module was implemented to model natural flow in the basin. HDS allowed for the explicit representation of the contributing area dynamics of prairie potholes which significantly impact the hydrology of the Milk River. The model was then used to run an ensemble of statistically downscaled future climate scenarios based on the CMIP6 models. Explicitly representing prairie potholes under future climate provided an opportunity to examine how non-contributing area might change in the future. We present an evaluation of historical model performance, a future climate analysis of streamflow in the basin, and the implications of the future climate conditions on apportionment practices in the basin. Results from this research will inform IJC decisions on future practices and infrastructure in this important transboundary basin and may add a new dimension to future practices as the effects of prairie potholes have never been explicitly considered.
How to cite: Coderre, P., Ahmed, M. I., Keshavarz, K., and Pietroniro, A.: Implementation of a hysteretic depression model to assess future water availability in the St. Mary and Milk River transboundary basin, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12597, https://doi.org/10.5194/egusphere-egu25-12597, 2025.
The Upper Danube Basin upstream of Vienna, which can be regarded as the water tower of the Danube region, has a long history of human influence on river flow, from land use changes to hydropower development and today’s anthropogenic climate change. At the same time, the civilizing activities in the basin also have included the collection of scientific data, leading to remarkably long and reliable observational hydro-meteorological time series by Swiss, German and Austrian hydro-meteorological services and authorities.
Based on these observational data sets, this contribution presents exceptionally long hydrological simulations for the Upper Danube Basin, spanning from the time of the industrial revolution (1870) to the record-breaking hot years of the last decade (until 2023). An existing, well-established model for the Danube basin (Kling et al., 2012, Stanzel and Kling, 2018) was re-applied, but with new input data sets and new parameterization. This long simulation time-series (1870-2023) allows a rigorous testing of the hydrological model’s capabilities to adequately simulate non-stationary conditions, by evaluating different periods with specific characteristics and the representation of slow changes and long-term trends. The simulations facilitate the analysis of complex changes in the water balance and the impact on river discharge, both in the past and in the future.
In the framework of the climate change impact research project STREAM (Storylines of Danube Streamflow), the hydrological model of the Upper Danube will be applied to simulate future Danube discharge conditions based on the latest CMIP6 climate model projections.
References:
Kling H, Fuchs M, Paulin M. 2012. Runoff conditions in the upper Danube basin under an ensemble of climate change scenarios. Journal of Hydrology Vol. 424-425, p. 264-277
Stanzel P, Kling H. 2018. From ENSEMBLES to CORDEX: Evolving climate change projections for Upper Danube River flow. Journal of Hydrology Vol. 563, p. 987-999
How to cite: Kling, H., Stanzel, P., Lerche, F., and Ossó, A.: Hydrological simulation of Danube River discharge over the last 150 years and future projections with CMIP6 until 2100, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18525, https://doi.org/10.5194/egusphere-egu25-18525, 2025.
Riparian strips form a transition zone between terrestrial and freshwater ecosystems providing essential ecosystem services. Healthy strips are crucial for the stability and sustainability of ecological systems. Riparian zones have major environmental importance because these could be interpreted as collision zones of transporting pollutants (on both surface and subsurface) from the land to the freshwater. According to that riparian zones have irreplaceable effect on sediment- and nutrient mitigation and securing freshwater ecosystem biodiversity.
Despite their vital importance, the research community paid less attention on riparian strips. Policy-level regulation of land use and related pollutant emissions within strips is also lacks. As a result, degradation of riparian habitats is still increasing.
In this study, we determined of a critical delineation distance of riparian strip with the fixed buffer strip approach. This was based on the analyses of almost 5000 computed local groundwater – surface water gradients in four counties of the Danube River Basin. We evaluated the actual and historic land use conditions within the derived riparian strips. To establish and understand the motivations and cause-effect relationship behind the land use arrangement, we examined the vegetation biomass production inside and outside the defined zone. In addition, to gain a more accurate understanding of the water balance processes of the riparian strips, we performed three types of trend analysis on the groundwater well time series.
Based on our results, the distance from the watercourse influenced the historical trends of groundwater wells. We highlighted in our results, that the proportion of agricultural areas exceeds national level ratios concerning natural land cover types within the riparian strips. For most countries of the Danube River Basin, the agricultural land use category shows up to almost 10% increase within the riparian strips compared to outer zones regarding a crop yield indicator. This means, that within the riparian strips, areas with significant potential for provisioning services are primarily exploited, to the detriment of regulating services. This revealed conflict is also an opportunity that affects the feasibility of several European Union strategies (Water Framework Directive, Biodiversity Strategy until 2030), by pointing out potential restoration sites.
How to cite: Decsi, B., Koncsos, L., and Kozma, Z.: Exploring hydrological- and environmental indicators with their coupled consequences on ecosystem services relationships for the riparian zones of Danube River Basin, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6007, https://doi.org/10.5194/egusphere-egu25-6007, 2025.
This work quantifies the hydrological alterations caused by climate change on 11 major basins of the Danube River. The quantification is performed using the natural discharge (i.e. without water demand and abstractions) between the years 1990 and 2020 as a reference period and the projected discharge between 2030 and 2100 for the SSP-RCP climate change scenarios SSP1-2.6, SSP3-7.0 and SSP5-8.5. Discharges for the reference period and the projections have been simulated with CWatM, a grid-based hydrological model. CWatM was calibrated and tailored for the Danube basin for this case study. The reference period was simulated using as input dataset hydrometeorological data from Multi-Source Weather (MSWX) product while the projected discharge was simulated using ISIMIP3b climate change hydrometeorological datasets for 5 global circulation models (GCM).
Past and future hydrological regimes were used to compute a set of indices from the Hydrological Nature Conservancy Indicators of Hydrologic Alteration. These indices quantify the in-stream disturbance regime and the average habitat conditions. Indices were computed using the discharge at the outlet of 11 Danube sub-basins. The differences between the reference and future hydrological regimes were assessed as percentage differences. The percentage differences were calculated for each combination of SSP-RCP—GCM, thus allowing to assess the uncertainty of the results.
The results show marked differences in the projected impacts for the different sub-basins. Overall, the basins in the lower course of the Danube are the most affected under all climate change scenarios, while those in the middle course are somehow more stable. Nevertheless, all sub-basins exhibit a moderate to strong hydrological alteration for at least two indices.
How to cite: Politti, E., Catania, C., Artuso, S., and Kahill, T.: Projected Hydrological Alterations in the Danube River Basin under Climate Change, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3743, https://doi.org/10.5194/egusphere-egu25-3743, 2025.
Water, an indispensable resource for sustaining life and ecosystems, is increasingly at the center of geopolitical tensions, particularly in transboundary river basins. This study introduces "Hydrocide" as a conceptual framework to analyze and address the deliberate manipulation of water resources that exacerbates socio-environmental vulnerabilities in downstream nations. Hydrocide captures the intersection of environmental injustice, resource governance, the root causes of disasters, and the socio-political dynamics of water management, framing such actions as a form of systemic oppression with long-term consequences. Rooted in the principles of the Universal Declaration of Human Rights, and no natural disasters, this framework reconceptualizes water crises as socially constructed phenomena, shaped by inequitable policies and governance rather than natural inevitabilities.
Using the Ganges-Brahmaputra-Meghna (GMB) basin as a case study, this work examines the implications of upstream water management practices, including dam and barrage construction, water diversion, and the absence of equitable transboundary agreements. The downstream impacts on Bangladesh, a riparian nation heavily reliant on these rivers, include seasonal water shortages, artificial floods, ecological degradation, and socio-economic instability. These challenges are compounded by the dual forces of climate change—such as glacier melt and extreme monsoonal rains—and population growth, which intensify demand and strain water availability.
The framework of "Hydrocide" offers a novel lens to conceptualize these challenges, bridging the discourse between environmental justice and global governance of shared water resources. This approach emphasizes the need for cooperative mechanisms, transparent data sharing, and equitable water distribution policies to mitigate the cascading impacts of hydrological mismanagement. By integrating hydrocide into transboundary water crisis management, this study aims to inform sustainable and fair solutions for one of the most vulnerable river basins in the world, while providing a transferable framework applicable to global contexts.
How to cite: Ahmed, B.: Hydrocide: A Conceptual Framework for Transboundary Water Crisis Management , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-569, https://doi.org/10.5194/egusphere-egu25-569, 2025.
Accurate water balance is important for both water resource management and nutrient emission modeling. This study compares the water balance results from the MONERIS (Modeling Nutrient Emissions in River Systems) model with those from WetSpass (Water and Energy Transfer between Soil, Plants, and Atmosphere under quasi-Steady State) and field-measured data in Hungary's Koppány basin, a 660 km² hilly catchment. MONERIS uses empirical equations of water balance components: precipitation, evapotranspiration, runoff, and groundwater recharge. WetSpass adds spatially explicit hydrological and land-use information. The most characteristic features of the Koppány catchment are a high proportion of agricultural land, large-field arable farming of approximately 63% of the total area of the catchment and total agricultural lands of 72% of the total area of the catchment, and relatively low population density of approximately 29 inhabitants per square kilometer (inh./km²). The Koppany catchment has a mean annual flow of approximately 1.26 m³/s. Water quality is seriously affected by eroding soil conditions within the catchment and severe point-source contamination by wastewater effluents: treated wastewater makes up approximately 8% of the total flow.
The present study furthers nutrient emission modeling through showing the relative strengths and weaknesses of lumped empirical and spatially distributed process-based techniques.
Keywords: Water Balance, MONERIS, WetSpass, Koppány Catchment , Nutrient Emission modeling
How to cite: Almohtaseb, F. and Kardos, M.: Comparative Assessment of Water Balance Calculations: MONERIS and WetSpass Models in the Koppány Catchment, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9132, https://doi.org/10.5194/egusphere-egu25-9132, 2025.
Large-scale hydrological models simulate the water cycle for regions, countries, and continents. The choice of input data directly impacts the accuracy of these models' final output and the spatial and temporal pattern, as well as the quality of data (air temperature and precipitation), influences the quality and pattern of water availability estimates. It is essential to acknowledge that the accuracy of these estimates depends on the input quality of the data used.
In this regard, precipitation and air temperature gridded European Meteorological Observations (EMO1) datasets specifically used for hydrological modeling inputs (CWATM) are evaluated over the Danube River Basin (DRB). The observation data (air temperature and precipitation) from 9 different countries within the DRB are used for the EMO1’s evaluation. The performance of the datasets was evaluated at daily, monthly, and annual scales, using Pearson Correlation (r), root mean square errors (RMSE), mean absolute errors (MAE), Nash Sutcliffe Efficiency (NSE), Percent Bias (PBIAS), and Kling Gupta Efficiency (KGE) criterion.
The results showed the range of temperature differences varies between approximately -3°C and +2°C. This reflects both underestimations and overestimations by EMO1 compared to observations. The median differences are close to 0 for most months, indicating the EMO1 model is generally unbiased or well-calibrated overall. Larger variability and more outliers occur in warmer months (e.g., May–August), suggesting the model may struggle with accurately capturing summer temperature dynamics. For precipitation, the median is slightly positive, suggesting a systematic overestimation of precipitation during the summer months. This could be due to the model overestimating convective rainfall.
By identifying the periods where the EMO-1 deviates most from observations, researchers can target specific processes for calibration or refinement, which is especially important for hydrological applications
Acknowledgment
This work was supported as part of DANUBE WATER BALANCE, an Interreg Danube Region Programme project co-funded by the European Union.
How to cite: Amihăesei, V., Cheval, S., Chitu, Z., Radu, A., Petre, C., Ács, T., Kozma, Z., György, M., and Chendeș, V.: Evaluation of European Meteorological Observations gridded data of air temperature and precipitation amount over Danube River Basin (1990-2022) , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16995, https://doi.org/10.5194/egusphere-egu25-16995, 2025.
Over 310 transboundary river basins span across 153 countries, covering 47.1% of the Earth's surface, including 52% of the world’s population, and accounting for almost 60% of the world’s freshwater flow. These river systems flow across political boundaries, creating a complex web of environmental, political, economic and security-related interdependencies. As riparian countries have their respective values, priorities and interests towards shared waters, managing transboundary water resources is a long-term and often challenging process. With the increasing hydrological variability due to climate change, accelerated population growth/urbanization, geopolitical instability, economic development, and global epidemics, the uncertainty in transboundary river water management has further intensified. Existing research offers a broad range of empirical studies based on detailed water event data but has not yielded universally applicable conclusions that can be generalized across all transboundary river basins. News media articles provide a full process understanding of the development of water events, recognized as a valid proxy to track societal values or public opinion on water issues, as well as reflect nuanced insights. This study, based on the constructed global transboundary river water conflict and cooperation news media articles dataset covering 105 out of over 310 transboundary rivers worldwide, with a time span from 1977 to 2022, employs text analysis methods to explore and identify patterns of transboundary river water conflict and cooperation dynamics. The findings will contribute to a deeper understanding of the dynamics on global transboundary river conflict and cooperation and provide insights for promoting water cooperation.
How to cite: Wang, J., Wei, J., Wei, Y., and Tian, F.: Identifying Patterns of Transboundary Water Conflict and Cooperation Dynamics Based on News Media Articles, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4702, https://doi.org/10.5194/egusphere-egu25-4702, 2025.
Austria has set an ambitious goal to produce 100% of its electricity from renewable sources by 2030. To support this transition and to enable informed energy planning and optimized resource use in the future a detailed national-wide distributed hydrological model of Austria was set up to assess the changes in water balance in more than 50000 river profiles. The model operates on a daily time step and simulates the hydrological processes on a 2x2 km grid in cells that are aggregated into sub-basins of a mean area of 115 km2 and routed along the pre-defined river network. The meteorological inputs for the model comprised high-resolution grids interpolated from station datasets for areas with available observations and low-resolution EOBS grids for small areas outside of Austria with small coverage of available station data.
To account for anthropogenic influences, reservoir operation and water transfer modules were incorporated, significantly improving model performance in affected regions. The model was calibrated and validated using a newly proposed step-wise iterative procedure within the 1991-2020 period, focusing on the interannual flow regime and the monthly water balance. Significant improvements in the robustness of the model were achieved by incorporating remote sensing products of snow cover and soil depth reducing the number of free parameters. The model achieved a median Nash-Sutcliffe efficiency of 0.9 across 532 Austrian profiles, calculated for the interannual regime.
Future water balance changes were projected for 2066–2075 using the MPI-M-MPI-ESM-LR_r1i1p1_SMHI-RCA4 climate model under RCP 4.5 and RCP 8.5 scenarios. A delta-change approach was used to adjust historical air temperature and rainfall records, minimizing biases associated with climate model projections. Results indicate increased mean monthly river discharges during winter and little to no change or slight decreases during summer in most river profiles. These changes are more pronounced in smaller mountainous catchments, where rising air temperatures lead to reduced snowpack accumulation and shorter snow cover durations.
How to cite: Valent, P., Komma, J., and Blöschl, G.: Modelling Austria’s water future: A transboundary national-scale distributed hydrological model for climate change impact assessment, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4039, https://doi.org/10.5194/egusphere-egu25-4039, 2025.
Historical flood events occurred before the begin of systematic flow records, represent valuable information that should be considered in flood frequency analyses. However, in most cases historical data is still stored in printed volumes and therefore not easily accessible and ready-to-use for hydrological analyses. The aim of this study is to compare the largest historical floods in the Danube and Main catchments to modern (i.e. between 1950 and 2022) floods in terms of their spatial, temporal and causal carachteristics. Here we collect, digitize, and compile a dataset of the largest historical flood events in the Danube and Main catchment between 1845 and 1950. The newly developed dataset contains daily and peak discharge and water level measurements observed at several locations for 13 and 9 flood events in the two catchments. Flood hydrographs were also recovered at several locations in the Danube catchment. Using the developed dataset, we compare the characteristics of the historical flood events to the characterisitcs of modern large flood events. The findings show that the historical flood discharges are among the largest ever measured in the two catchments and that large floods occur more frequently in summer than in the past. In summary, this work reviews the spatial, temporal and causal characteristics of these very large historical events in comparison with recent events and discusses the implications for flood hazard assessment.
How to cite: Bertola, M., Valent, P., Komma, J., and Blöschl, G.: Characteristics of historical extreme floods in the Danube and Main catchments in Austria and Germany compared to modern ones, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6690, https://doi.org/10.5194/egusphere-egu25-6690, 2025.
The Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover product is well-suited for hydrological applications due to its reliable accuracy and daily accessibility. However, the MODIS snow product is anticipated to be replaced by the Visible Infrared Imaging Radiometer Suite (VIIRS) snow cover product soon. Therefore, a thorough and accurate evaluation of this product is essential to ensure its suitability for future hydrological applications.
This study aims to assess the accuracy of the VIIRS snow product across Austria (observations at 631 climate stations) and within a small experimental catchment, the Jalovecký Creek catchment in northern Slovakia, using extensive snow course measurements conducted at both open and forested sites between January 2012 and August 2021. In the VIIRS snow cover product, the Normalized Difference Snow Index (NDSI) is used for snow detection. A threshold of NDSI (TNDSI) is needed for distinguishing snow from snow-free land. Based on the daily snow depth observations from climate stations/snow course locations, the best NDSI threshold (BTNDSI) is firstly determined through a detailed sensitivity test (100 different TNDSI from 0.01 to 1.0 with a step of 0.01). The overall accuracy (OA) of VIIRS data is then evaluated based on the BTNDSI and by comparison with the daily C6 MODIS snow cover dataset. The assessment of the BTNDSI/OA is performed for all climate stations/snow course locations, as well as for different groups of stations representing different physiographic and land cover conditions. The results will compare the seasonal and topographical variability of mapping accuracy and the mapping threshold. We will also compare the mapping accuracy at open and forested sites.
This work was supported by the Slovak Research and Development Agency under Contract No. APVV-23-0332, the VEGA Grant Agency No. 2/0019/23, and the Danube Region Programme: DRP0200156 Danube Water Balance.
How to cite: Sleziak, P., Danko, M., Jančo, M., Holko, L., and Valent, P.: VIIRS snow mapping accuracy at regional and catchment scale, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8225, https://doi.org/10.5194/egusphere-egu25-8225, 2025.
Climate change is leading to alterations in low-flow conditions and droughts, while societal factors like urbanization are intensifying these challenges. This underscores the urgent need for a deeper understanding and more effective management of water shortages in the Danube main stream. Innovative modelling tools addressing water demand are able to assess the allocation between relevant demands including agriculture, industry, hydropower, ecology and navigation during low flow periods. The STARS4WATER project deals with the complex challenges faced by the transboundary Danube river basin. The study area encompasses 19 riparian countries, covering a total area of 801,463 km² with diverse topographic and climatic characteristics. Stakeholders actively participated in identifying drought and low flows as key issues for water management in the basin. The upper Danube is particularly influenced by glaciers and snow, which are significant for low flows during summer, and these dynamics are expected to change under future climate scenarios. Lower Danube is expected to face increased drought risk in combination with rising agricultural water demand. As a result, the River Basin Simulation (RIBASIM) model was initiated for the entire basin. The RIBASIM model, a node-link model for simulating and balancing water availability, allocation and use, was employed including the present state. Inflow nodes for sub-catchments representing the boundary conditions regarding water availability were determined using the wflow_sbm model, a grid-based rainfall-runoff model. Input data comprised discharges from defined sub-basins for the period 2010 to 2020 at a resolution of 10 days. On the demand side, the focus was on the Danube main stream, including water supply for cities, major industrial demands in Germany and Austria as well as nuclear power plants, and specific irrigation areas. Those are represented by water demand and water abstraction nodes. Critical low flow nodes, essential for minimum flow for navigation, were also identified. Explicit demands were collected from statistical authorities, non-governmental organizations, academic papers and established consensus. Simulated discharges, demands, supplied demands (i.e. water use), and shortages for the period 2010 to 2020, were verified by a plausibility check and sensitivity analysis. It serves as a starting point for future scenario-based analyses including e.g. the effect of glacier retreat and water allocation and use priority setting during low flows. The study emphasizes the need for comprehensive local water demand data collection river basin-wide and enhanced transboundary cooperation to tackle water management challenges in the Danube River basin, including adherence to national and EU-wide statistical standards considering water use and demand. In particular, data on water demand from industries and agriculture are essential to identify hotspots for shortages in the Danube during droughts and low flows more effectively. The finding is relevant for implementing future scenarios related to climate, hydrology, socio-economic factors, and water resource management. By better unlocking data availability and improving data resolution and incorporating future projections, more accurate and practical insights for managing water resources in the face of evolving environmental and societal pressures are achievable.
How to cite: Graf, T., Glas, M., Monji, F., Klösch, M., Preiml, M., ter Maat, J., Toma, A., Scrieciu, A., and Habersack, H.: RIBASIM Danube: Modeling water allocation in the Danube Basin with a focus on low-flow conditions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6640, https://doi.org/10.5194/egusphere-egu25-6640, 2025.
This study focused on developing an aggregated hydrological model that is robust, computationally efficient, and capable of accurately describing groundwater resource dynamics. The model is based on the Kovács retention curve and incorporates evaporation using the low-data-demand Dunay–Varga-Haszonits method while accounting for the impact of regional subsurface flow systems. A central hypothesis of the study posits that the infiltration of precipitation into groundwater can be effectively modeled using longer, aggregated time steps (14 days in this case), by describing average changes within each time step without requiring detailed vertical profiles. Furthermore, we hypothesized that the aggregated average soil moisture, which influences evapotranspiration, can be accurately described based on the equilibrium retention curve adjusted to groundwater levels, using the average groundwater position during the aggregated interval.
The developed model enables nationwide analyses involving data from hundreds of monitoring wells, providing acceptable computational speed and accuracy. The study area was the Great Hungarian Plain, a region highly vulnerable to groundwater fluctuations due to its agricultural significance. The analysis was based on the FORESEE meteorological database, which integrates the results of several climate models covering the period 1960-2100. Future groundwater level changes under different climate scenarios were effectively analyzed. Simulations were conducted for more than 400 monitoring wells, resulting in projected trends for groundwater level changes. The findings indicate significant adverse changes in groundwater levels by 2050 under both RCP 4.5 and RCP 8.5 climate scenarios. The model represents a valuable tool for sustainable water resource management and for assessing the impacts of climate change on groundwater levels.
Project no. TKP-6-6/PALY-2021 has been implemented with the support provided by the Ministry of Culture and Innovation of Hungary from the National Research, Development and Innovation Fund, financed under the TKP2021-NVA funding scheme. The research presented in this abstract was carried out within the framework of the Széchenyi Plan Plus program with the support of the RRF 2.3.1 21 2022 00008 project.
How to cite: Murányi, G. and Koncsos, L.: Innovative Hydrological Modeling for Groundwater Level Projections in the Carpathian Basin, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18248, https://doi.org/10.5194/egusphere-egu25-18248, 2025.
In Northern Lithuania, Biržai and Pasvalys districts, significant karst activity occurs due to gypsum-rich Devonian dolomite formation near the surface. Over time, water dissolves the gypsum, creating underground cavities that cause sinkholes when the ground collapses. The region has more than 11 thousand sinkholes, some densely clustered, with typical dimensions of 10–20 meters in diameter and 5 meters deep.
Groundwater level monitoring in Lithuania's karst regions was conducted in nine wells by the Lithuanian Geological Survey. Monitoring activities began as early as 1965 and have expanded over the decades, with newer installations starting in 2004. The monitored wells vary in depth, ranging from 10.7 to 46 meters in confined and unconfined aquifers.
In addition to water levels, the major ionic composition is analyzed in samples from all wells except Biržai MS (Well No. 35994), providing valuable data on groundwater chemistry and its interaction with karst processes.
Lithuania's karst region is located in a transboundary area shared with Latvia, making it a region of joint environmental and scientific interest. This area is currently a focus of the GRANDE-U (Groundwater Resilience Assessment through Integrated Data Exploration for Ukraine) project, which aims to enhance the understanding and management of groundwater through advanced techniques. One of the key aspects of this project is the modelling of groundwater parameters using machine learning (ML) algorithms, which are further complemented by GRACE (Gravity Recovery and Climate Experiment) satellite data.
Karst systems are hydrogeologically characterized by fractured structures that respond rapidly to groundwater level changes. This sensitivity makes them particularly suitable for observation using gravitational data, as fluctuations in groundwater levels can be detected through variations in the Earth's gravitational field. The transboundary nature of the Lithuanian and Latvian karst regions underscores the importance of collaborative efforts like GRANDE-U to ensure sustainable water management and protect the unique geological and hydrological characteristics of this area.
The GRANDE-U “Groundwater Resilience Assessment through Integrated Data Exploration for Ukraine” (No. 2409395) project unites researchers from six countries - the U.S., Ukraine, Poland, Lithuania, Latvia, and Estonia. Vilnius University has received funding from the Research Council of Lithuania (LMTLT), agreement No. S-IMPRESSU-24-3.
How to cite: Samalavičius, V., Žaržojus, G., Kunsakova, A., and Arustienė, J.: Lithuanian Karst Region Hydrogeology: Available Data and Future Research Prospects, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11761, https://doi.org/10.5194/egusphere-egu25-11761, 2025.
The rapid advancement of artificial intelligence (AI) opens new opportunities across various scientific disciplines, including hydrogeology. AI-based methods, particularly machine learning (ML), are increasingly utilized to address complex, non-linear relationships in hydrogeological data, offering improved accuracy and efficiency over traditional approaches. This study is the first attempt to apply AI techniques to assess hydrogeological parameters (hydraulic conductivity (k)) in Lithuanian soils, aiming to compare the accuracy of traditional empirical formulas (EFs) and modern computational approaches.
Hydraulic conductivity (k) is a critical parameter for evaluating soil permeability and water movement in porous media, which is widely used in hydrogeological modelling, contaminant transport, and geotechnical design. This research compares the predictive performance of six ML algorithms (Elastic Net, Gradient Boosting Regressor, Huber Regressor, K-Neighbors Regressor, Multi-Layer Perceptron Regressor, Random Forest Regressor) with empirical formulas using a dataset of 282 unique soil samples. Grain size distributions and particle diameters were used as features (input parameters) for ML models to predict k values.
Statistical metrics reveal that ML models significantly outperformed EFs, achieving r-squared of 0.36–0.46, compared to 0.10–0.33 for EFs. However, some ML models displayed signs of overfitting, and performance varied depending on input feature combinations, with optimal models requiring 4–8 parameters. The study also highlights the limited size and diversity of the dataset as a key constraint, underscoring the need for a more extensive and diverse soil database for robust ML model development.
This pioneering effort demonstrates the potential of AI to enhance and revise geological research in Lithuania, suggesting that ML can provide more accurate and scalable solutions for other hydrogeological and engineering geology problems.
How to cite: Žaržojus, G., Samalavičius, V., Vanhala, E. K.-M., Lekstutytė, I., Gadeikienė, S., and Gadeikis, S.: Machine learning applications in hydrogeology, the case study of Lithuanian soils' hydraulic conductivity, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8695, https://doi.org/10.5194/egusphere-egu25-8695, 2025.
The pollution of our natural waters is an increasingly urgent and crucial problem.Both point and diffuse pollution can enter the river basin from a variety of sources.The streamflow - and the resulting pollutant loads - exhibit abrupt changes in behavior influenced by rainfall and surface run-off.A significant portion of the pollution is associated with short-duration event flows, which cause sudden, substantial increases in streamflow. The primary objective of my thesis is to refine the load estimation method using baseflow separation methods, specifically the Lyne-Hollick (L-H.) and Eckhardt methods. The methods were applied at two measuring stations of the Koppány stream in Somogy County, Törökkoppány and Tamási.
In addition to hourly water flow measurements, electrical conductivity and turbidity are continuously monitored in the area at five-minute intervals. A permanent point source of pollution is the treated wastewater of Balatonlelle, which is discharged into the Koppány stream as a contribution to the baseflow load. The calculation process benefited significantly from the stratified sampling method used, in which an automatic sampler is activated at a defined water flow threshold. This enables separate treatment of samples from baseflow and high flow, allowing better estimations of contaminant concentrations during high flow conditions and providing a more accurate load estimation.
The estimated baseflow-index for Törökkoppány is 0.60 (L-H.) and 0.57 (Eckhardt) while for Tamási, it is 0.86 (L-H.) and 0.57 (Eckhardt). In terms of micropollutants, metals and pesticides dominate the mass for both methods, associated with high flow events.Meanwhile, pharmaceuticals, phenols, and PFAS compounds, linked to anthropogenic sources, are more prominent in the baseflow load. Based on the L-H. filter, Törökkoppány receives 91.7% of its annual 4634 kg metal compound load during high flow events. The total pesticide load is 87 kg per year, with 98% attributed to high flow events. Results from the Eckhardt filter align closely with the aforementioned findings. Based on the L-H. method at Tamási, the estimated annual metal load is 3488 kg, with 62% from high water events. while the Eckhardt method reports an annual metal load of 7408 kg (88% from high flow). Total pesticide emissions are 63kg/year (L-H.), predominantly from high flow (88%), and 171 kg (Eckhardt) with 97% attributed to high flow. Phenols, PAH and PFAS compounds are baseflow-related and do not exceed 1-2kg/year.
To understand why the two methods show such different results for Tamási, the Rimmer-Hartmann method could be an appropriate solution.
Funding: The research presented in the article was carried out within the framework of the Széchenyi Plan Plus program with the support of the RRF-2.3.1-21-2022-00008 project. The research was co-financed by the National Research Development and Innovation Office (NKFIH) through the OTKA Grant SNN 143868 and by the European Union through the RRF-2.3.1-21-2022-00004 Artifical Intelligence National Laboratory project.
How to cite: Lajkó, T., Clement, A., and Kardos, M. K.: Hazardous Substance Load Estimation in a Small Catchment Using Baseflow Separation and Composite Sampling, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-21853, https://doi.org/10.5194/egusphere-egu25-21853, 2025.
