Traditional hydrologic models often treat wetlands as an aggregated unit, failing to capture dynamic wetlandscape processes, including seasonal expansion-contraction cycles and evolving connectivity patterns that fundamentally alter watershed flow generation. We hypothesized that the inclusion of wetlandscape patterns and behavior can improve prediction of watershed hydrology. Here, we link wetlandscape characteristics to hydrologic signatures across 200 gaged watersheds in the Prairie Pothole region in the US. Static and dynamic landscape metrics capturing wetland position, configuration and variability were determined using the Dynamic Surface Water eXtents from Harmonized Landsat Sentinel-2 (DSWx-HLS) product and the National Wetlands Inventory while hydrologic signatures were derived from daily discharge gages over twenty years of observation in watersheds with a range of wetland densities. Regression models explained hydrologic signature magnitude and variability using and wetlandscape metrics together with climate, topography, land cover, as predictors. The addition of wetlandscape configuration explained significant additional variance beyond traditional watershed characteristics for multiple signatures. Variable importance analysis revealed wetland spatial patterns ranked among top predictors for six of eight signatures examined. These findings demonstrate that incorporating spatially-explicit wetlandscape dynamics substantially improves hydrologic prediction capabilities across multiple temporal scale
How to cite: Cheng, F.: Wetlandscape Configuration and Structure as Predictors of Watershed Hydrologic Signatures, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22855, https://doi.org/10.5194/egusphere-egu26-22855, 2026.
Excessive nitrogen (N) inputs from agricultural intensification, wastewater, and atmospheric deposition pose a severe threat to European ecosystems and public health, with N levels in over 57% of freshwater monitoring stations exceeding thresholds for good ecological status. While traditional management practices focus on reducing inputs, nature-based solutions (NBSs) like wetlands offer powerful, cost-effective filtration by facilitating denitrification in their carbon-rich, anoxic soils. This study presents a novel, pan-European modeling framework that combines high-resolution N surplus data, historical wetland distribution, and projected land-use changes to quantify the current and potential N-removal capacity of wetlands across the EU27 and neighboring countries.
The analysis estimates that existing European wetlands currently remove approximately 1,000 kt of nitrogen per year, a service that prevents riverine N loads to the sea from being 25% higher than they are today. Despite this contribution, Europe remains a hotspot for wetland loss, having drained roughly 70% (~78 Mha) of its historical wetland area, primarily for agricultural expansion.
To address current pollution gaps, the study evaluates three restoration scenarios designed to meet water quality targets while balancing agricultural productivity. The most ambitious Restoration scenario - restoring 27% of wetlands historically drained for agriculture (3.2% of total land area) - could reduce N loads to the sea by 36%. However, the study identifies a more efficient strategy, which targets restoration on lands projected to be abandoned by 2040. This approach yields a 22% reduction in total N loads and enables major rivers like the Rhine, Elbe, and Vistula to meet water quality targets with minimal impact on agricultural output.
Cost-benefit analysis indicates that while restoration costs are significant - ranging from €55-358 billion per year for the full scenario - the co-benefits of ecosystem services, such as carbon sequestration and flood regulation, often outweigh these expenses. Ultimately, the findings highlight that spatially targeted wetland restoration is a vital, policy-relevant tool for achieving the European Green Deal’s goals for water quality, biodiversity, and climate sustainability. However, the study concludes that in the most heavily polluted basins, wetland restoration must be paired with continued reductions in diffuse N sources to reach good ecological status.
How to cite: Bertassello, L. E., Basu, N., Maes, J., Grizzetti, B., Notte, A. L., and Feyen, L.: The Critical Role of Wetland Conservation and Restoration in Mitigating Nitrogen Pollution Across European River Basins, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-23188, https://doi.org/10.5194/egusphere-egu26-23188, 2026.
Coastal wetlands represent invaluable “carbon banks”, as they naturally capture and store atmospheric carbon under water-logged conditions, where dead plant material decomposes very slowly, and organic layers build up in the soil. However, when drained or perturbed, wetlands can switch from carbon sinks to major sources, making monitoring and restoring degraded wetlands a worldwide environmental priority. Water table level plays a key role in regulating carbon exchange, but uncontrolled rewetting works do not suffice in restoring their optimal status. The reason is that forecasting beneficial effects of wetlands restoration is often challenged by the complexity of coupled water-soil-vegetation dynamics that both regulate soil respiration rate and shape micro-scale morphological features in the short and long terms. As a result, a significant number of studies have reported unexpected and significant failure outcomes in restoration works. Existing modeling frameworks generally neglect the spatial heterogeneity of wetland morphology and rely on heavy implementations of empirical functions, which limits model predictions to be site-specific. In this work, we adapt a landscape evolution model to explicitly simulate spatial wetlands morphology, accounting for coupled water, sediment, and vegetation dynamics. Carbon fluxes are then evaluated in a spatially explicit manner accounting for the high-resolution simulated heterogeneity of water table level, sediment elevation, and vegetation density. The modelled surface morphology is first compared, through standard river network metrics, with satellite images of tidal wetlands that exhibit different levels of river channeling. The simulated spatially-distributed carbon fluxes suggest that highly branched morphologies promote optimal water distribution and enhance carbon sequestration. These trends are confirmed by comparing simulated ecosystem fluxes with flux-tower eddy covariance measurements in several tidal wetlands.
How to cite: Miele, F., Kargere, B., Aeppli, M., and Bonetti, S.: Tidal branching wetlands morphology and its role on water-carbon budget cycles , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19693, https://doi.org/10.5194/egusphere-egu26-19693, 2026.
Sea level rise and storm surges affect coastal forests along low-lying shorelines. Salinization and flooding kill trees and favour the encroachment of salt-tolerant marsh vegetation. The hydrology of this ecological transition is complex and requires a multidisciplinary approach. Sea level rise (press) and storms (pulses) act on different timescales, affecting the forest vegetation in different ways. Salinization can occur either by vertical infiltration during flooding or from the aquifer driven by tides and sea level rise. Here, we detail the ecohydrological processes acting in the critical zone of retreating coastal forests. An increase in sea level has a three-pronged effect on flooding and salinization: It raises the maximum elevation of storm surges, shifts the freshwater-saltwater interface inland, and elevates the water table, leading to surface flooding from below. Trees can modify their root systems and local soil hydrology to better withstand salinization. Hydrological stress from intermittent storm surges inhibits tree
growth, as evidenced by tree ring analysis. Tree rings also reveal a lag between the time when tree growth significantly slows and when the tree ultimately dies. Tree dieback reduces transpiration, retaining more water in the soil and creating conditions more favourable for flooding. Sedimentation from storm waters combined to organic matter decomposition can change the landscape, affecting flooding and runoff. Our results indicate that only a multidisciplinary approach can fully capture the ecohydrology of retreating forests in a period of accelerated sea level rise.
How to cite: Fagherazzi, S., Nordio, G., Boaga, J., Cassiani, G., Michael, H., Pratt, D., Messerschmidt, T., Kirwan, M., and Stotts, S.: The Ecohydrology of Coastal Ghost Forests, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1338, https://doi.org/10.5194/egusphere-egu26-1338, 2026.
Hydrological variability is a key regulator of greenhouse gas (GHG) fluxes across wetland-cropland transitions in cultivated landscapes, acting directly through water table dynamics and indirectly via land-use change, yet the balance of these effects is poorly understood. In these landscapes, rapid shifts in soil moisture which may extend to fully saturated conditions, can trigger highly dynamic methane (CH₄) and carbon dioxide (CO₂) responses, particularly within transition zones. In very flat and highly cultivated regions such as the Argentinian Pampas, widespread flooding and land-use reversion to wetlands have been associated with hydrological changes linked to the historical expansion of croplands. The effects of this large-scale ecohydrological transformation on biogeochemical functioning are still unclear.
We measured CH₄ and CO₂ fluxes across wetland-cropland transitions spanning multiple land uses and moisture regimes using in situ GHG monitoring combined with a broad suite of soil physical and chemical parameters across multiple field campaigns. This approach captured a wide range of water table positions and trends and allowed assessment of hydrology-, soil-, and carbon-related drivers of flux variability.
Across the landscape, water table depth was the dominant control on CH4 fluxes, with wetlands exhibiting the highest values. CH₄ fluxes displayed a clear nonlinear response to hydrological conditions, with sharp increases once the water table approached the soil surface (-24 cm), indicating a strong threshold behaviour. While accounting for water table position reduced apparent differences among land uses, CH₄ fluxes remained systematically higher in wetlands and transitional zones than in croplands and pastures, demonstrating additional modulation by land-use–specific soil properties. Moreover, the sensitivity of CH₄ emissions to water table changes differed among land uses, with transitional zones and wetlands showing the strongest responses, highlighting their vulnerability to small hydrological shifts.
In contrast, CO₂ fluxes were primarily controlled by temperature and dissolved organic carbon availability and showed a comparatively weaker and more gradual response to moisture gradients, without clear threshold behaviour.
Overall, our results show that water table dynamics are the primary control on CH₄ flux variability at the landscape scale, while land use determines how strongly soils respond to hydrological change. These findings emphasize the importance of accounting for both hydrological variability and land-use transitions when assessing GHG emissions from ecosystems.
How to cite: Nevermann, S., Jobbagy, E., Nosetto, M. D., Houspanossian, J., Diez, F., Whitworth-Hulse, J. I., Niborski, M. J., Rufino, M., and Zarebanadkouki, M.: Hydrological thresholds govern methane flux variability across wetland-cropland transition landscapes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17179, https://doi.org/10.5194/egusphere-egu26-17179, 2026.
Wetlands play a crucial role in the global carbon cycle, both by sequestering large amounts of carbon in their soils and acting as a major natural source of atmospheric methane. Methane emissions depend strongly on soil temperature, substrate availability, and the depth of the water table relative to the soil surface, reflecting a balance between production, oxidation, and transport. Here we develop a simple mathematical model that captures how production and oxidation interact to control emissions. We condense these processes into a single ordinary differential equation, parameterised by water-table depth, soil temperature, and vegetation-derived carbon inputs, to mechanistically explore how these factors interact to control wetland methane emissions. Using emission data from six mid-latitude wetlands in the Prairie Pothole Region, we show that the model can reproduce seasonal and inter-annual variation in fluxes. Having established this agreement, we employ the model to investigate the conditions under which emissions are maximised. Peak fluxes consistently occur at or just above the soil surface and are strongly modulated by wetland-specific parameters, with oxidation acting as a significant sink in some systems. Importantly, we find that the temperature sensitivity of oxidation is a key determinant of both the magnitude and location of peak emissions. These results highlight how warming may shift emission dynamics, emphasising the need for site-specific and adaptive wetland management and restoration strategies.
How to cite: McNicol, G., Layton, A., and Basu, N.: Understanding the balance between methane production and oxidation from wetlands using a minimalistic emissions model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22857, https://doi.org/10.5194/egusphere-egu26-22857, 2026.
Wetlandscapes are fundamental social-ecological systems that provide a wide range of provisioning, regulating, cultural, and supporting ecosystem services. While the ecosystem services of provisioning and regulation of hydrological and biological functions have been the main focus of scientific investigation, wetlandscape cultural ecosystem services (WCES) are comparatively underexplored, despite their central role in shaping human–wetland(scapes) relationships, collective memory, and long-term conservation commitment. Understanding how wetlandscapes are perceived and valued by local communities is essential to reveal the societal foundations of stewardship and sustainable socio-ecological relations.
This contribution presents a participatory approach to the assessment of WCES developed within the wetlandscape composed of the Padule di Fucecchio, the largest inland wetland in Italy, and Lake Sibolla, one of the southernmost peatlands in the world, both located in Tuscany, involving stakeholders from the municipality, recreational centers, farms, the private sector, etc.
We develop a framework to elicit a shared, community-based vision of the wetlandscape, integrating place-based values, narratives, and relational dimensions with more conventional eco-hydrological representations. We find that although hydrologically and ecologically connected, these wetlands are characterized by complex histories, functions, and cultural meanings. They demonstrate how connectivity and integration can support both ecological and social benefits, providing a unique opportunity to explore how diverse social perceptions and values coexist within a single wetlandscape. This approach allows us to expand the conceptual boundaries of wetlandscapes beyond purely biophysical definitions, framing them as dynamic socio-ecological systems shaped by reciprocal interactions between water, ecosystems, and society with implications for wetland management and conservation.
Acknowledgements
The project DOWES has received funding from The Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (Sweden), the Agence Nationale de la Recherche (France), Engineering and Physical Sciences Research Council (United Kingdom), Ministero dell'Università e della Ricerca (Italy), Fundação de Amparo à Pesquisa do Estado do Amazonas (FAPEAM/Brazil), Secretaria de Estado de Desenvolvimento Econômico, Ciência, Tecnologia e Inovação (SEDECTI/Brazil) and the Amazonas State Government (Brazil)— call N. 026/2023 WATER4ALL 2023, and the European Union’s Horizon Europe Programme under the 2023 Joint Transnational Call of the European Partnership Water4All (Grant Agreement n°101060874).
How to cite: Bresci, E., Castelli, G., Piemontese, L., Renzi, N., Lucca, E., Villani, L., Mannucci, N., Pacetti, T., Caporali, E., Scaini, A., and Jaramillo, F.: Understanding Cultural Ecosystem Services of Wetlandscapes: Insights from Central Italy, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14595, https://doi.org/10.5194/egusphere-egu26-14595, 2026.
Wetlands are essential ecosystems increasingly threatened by human activities and climate change. This study presents a method for classifying and monitoring wetland habitats in the Čiližská Radvaň protected area using RGB drone imagery and the Natural Numerical Network (NatNet), a mathematically based supervised deep learning approach. The primary aim was to evaluate the effectiveness of NatNet in identifying target habitat types and to assess the impact of ongoing revitalisation efforts. Habitat types were classified using RGB drone imagery and ground-truth training polygons representing the dominant vegetation communities in the Čiližská Radvaň wetland. The NatNet achieved a training classification success rate exceeding 97%, allowing the creation of relevancy maps that successfully identify spatial habitat distribution. Relevancy maps verified in the field achieved a classification accuracy of 0.88 and an F1 score of 0.90 across all habitats. Results showed observable shifts in habitat extent and structure after one year of restoration, confirming the method’s suitability for detecting ecological changes in wetland environments.
How to cite: Ozvat, A. A., Sibikova, M., Sibik, J., Sigmund, J., Papco, J., Kollar, M., and Mikula, K.: Wetland Classification and Revitalisation Monitoring by Using Drone Data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11830, https://doi.org/10.5194/egusphere-egu26-11830, 2026.
Wetlands play a critical role in the global carbon cycle, functioning as major carbon sinks while also serving as important sources of greenhouse gas emissions. Yet, in most watershed-scale carbon cycling models, wetlands are either highly simplified or omitted altogether, limiting our ability to represent wetland hydrological connectivity and associated carbon dynamics. To address this gap, we developed WISE-Wetland, a spatially explicit watershed-scale carbon cycling model.
We first proposed an improved discretization framework that explicitly represents wetlands as independent hydrological units within a watershed and constructs a wetland routing network. Using this wetland-unit routing network and delineated wetland catchments, we quantified and analyzed key wetland attributes, including area, hydrological connectivity, and routing characteristics. Building on this framework, we integrated a wetland carbon cycling module into WISE (Watershed-based Integrated Simulator for the Environment) that explicitly accounts for wetland routing processes—water retention, water-level dynamics, and wetland carbon transformation, transport, and emission.
WISE-Wetland has been implemented across diverse catchments. Simulations for the northern Krycklan watershed show that explicitly incorporating wetland routing networks substantially reconfigures organic carbon transport pathways and fluxes, leading to a marked improvement in model performance. We also simulated wetland carbon emissions in the Cottonwood watershed, demonstrating that the model can resolve spatial gradients and heterogeneity in wetland CH₄ fluxes, providing a more robust basis for quantifying wetland methane emissions and characterizing their spatial variability. Because watersheds are fundamental units of water and material redistribution, explicitly simulating wetland carbon cycling at the watershed scale offers critical insights into how future, climate-driven hydrological changes may regulate wetland carbon source–sink dynamics. Overall, WISE-Wetland provides a novel framework for advancing quantitative assessments of wetland contributions to regional and global carbon balances.
How to cite: Liu, J., Xiao, D., and Liu, J.: WISE-Wetland: A spatially-explicit carbon cycling model for wetland watersheds, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12530, https://doi.org/10.5194/egusphere-egu26-12530, 2026.
Wetlands developing in semi-arid regions are increasingly affected by salinisation and trace element enrichment; processes that should increase in time with climate changes and anthropic activities. The Okavango Delta (Botswana) provides a rare example of a pristine wetland that nevertheless shows evidence of trace element contamination. This alluvial fan located in the SW termination of the East African Rift System is in the heart of an endoreic drainage network taking its source in Angola and having its outlet in the Makgadikgadi pans. Annual floods enter the Delta, creating permanent and seasonal swamps that isolate thousands of islands of various sizes and shapes. Subsurface (2 to 3 m deep) groundwaters in the Delta are known to be largely alkaline with pH values up to 9, dissolved inorganic carbon values up to 4400 ppm and elevated concentrations of dissolved metals and metalloids, some of which are toxic (arsenic up to 6 ppm, uranium up to 12 ppm, vanadium up to 4 ppm, etc.). A first model explained the formation of the saline groundwater through evapotranspiration of the fresh water brought by the annual flood followed by infiltration through the tree belts surrounding the many islands emerging from the wetlands. However, our recent trace-element geochemical studies of groundwater and sediment in the central part of the Delta, showed that groundwater composition could not result from a simple evapotranspiration of surface water, leading to the proposition of a two-aquifer model. In this model, the two aquifers are hydrologically and chemically separated by a clay-rich layer. The surface aquifer contains circumneutral pH fresh water while the subsurface aquifer is seal-capped by the clay layer and contains alkaline water. Following this initial result, the present study addresses the nature, composition and origin of salt deposits that have been described on several of these islands of the Delta, especially in its eastern, more humid region. For the first time, we provide a complete major and trace elements geochemical description of these salts and compare them to evaporites from the Makgadikgadi pans. We demonstrate that the composition of the Delta salts (essentially trona) is very different from that of the Makgadikgadi evaporites (mostly halite) but, in some points, similar to that of the alkaline groundwater previously described. Our main hypothesis is that surface water could represent a source for the salt deposits through a coupling of mechanisms involving evaporation and biotic/abiotic (bio)geochemical processes. Here alkaline groundwater could represent a testimony of past similar processes trapped under a clay-rich layer. The concentrations of trace elements in the Delta salts (As: up to 110 ppm, U: up to 12 ppm, V: up to 14 ppm) and potential toxicity to the environment and local populations will be discussed.
How to cite: Challier, V., Jolivet, M., Mazrui, N., Dia, A., Davranche, M., Dauteuil, O., Pattier, M., Petitjean, P., and Dutruch, L.: Beyond Expectations: Unusual Water and Salt Chemistry in the Okavango Delta (Botswana), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12221, https://doi.org/10.5194/egusphere-egu26-12221, 2026.
Floating vegetated wetlands play a vital role in improving water quality by filtering pollutants and mitigating eutrophication in lakes, rivers, and wastewater systems. Within these systems, solute transport is strongly influenced by the interaction between hydrodynamics, vegetation structure, and reactive processes such as biosorption; however, the mechanisms governing such interactions remain poorly understood. This study develops a novel mathematical model to elucidate the dispersion of reactive solutes in flows containing floating vegetation, incorporating reversible adsorption–desorption dynamics at the vegetation–water interface. The governing equations are upscaled using Mei’s homogenization technique to derive an effective dispersion coefficient that accounts for multiscale interactions between flow and reaction processes. Three key dimensionless parameters, namely the vegetation factor (α), partition coefficient (θ), and Damköhler number (Da), are identified as primary controls on the effective dispersion behavior. Results indicate that vegetation density modulates flow heterogeneity and mechanical dispersion, with sparse vegetation (α < 1) promoting molecular diffusion-dominated transport, while dense vegetation (α > 1) induces recirculation zones that suppress dispersion. Additionally, increasing Da enhances solute localization via faster reactions, whereas higher θ intensifies retention within the biofilm phase. The interplay among α, θ, and Da defines distinct transport regimes, revealing optimal combinations that balance mixing and reaction for efficient contaminant removal. These findings provide a mechanistic framework for designing and optimizing floating vegetated wetlands, enabling improved control of solute fate under varying hydrodynamic and biochemical conditions.
How to cite: Hossain, S. and W. Tsai, C.: Reversible Bio-Sorption and Solute Transport in Floating Vegetated Wetlands, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12214, https://doi.org/10.5194/egusphere-egu26-12214, 2026.
Wetlands are vital for mitigating climate change, but widespread conversion to agricultural land has disrupted their functioning in terms of soil carbon (C) and nitrogen (N) dynamics. This study examined the impact of land-use/cover change on soil N, C, their thermal stability, and C composition in Yala Wetland. Using a stratified random approach, soil samples were collected from permanently flooded, seasonally flooded, sugarcane, maize, and vegetable farms, across depths of 0-50 cm. Multi-Element Scanning Thermal Analysis (MESTA) was used to quantify C and N thermal stability, while solid-state 13C NMR spectroscopy characterized C composition. Results showed significant differences (P < 0.05) in SOC, nitrogen, and C:N ratios across land uses. Vegetable farms had highest SOC (117.83 ± 16.54 g kg-1) and N (7.34 ± 1.07 g kg-1), while sugarcane fields had the lowest (SOC: 13.58 ± 0.97 g kg-1; N: 1.07 ± 0.04 g kg-1). Seasonally flooded wetlands stored more SOC (98.51 ± 20.55 g kg-1) and N (5.31 ± 1.12 g kg-1) than permanently flooded wetlands, suggesting that alternate wet-dry cycles enhance humification and organic matter (OM) stabilization. Data showed dominance of thermally labile C (C < 400 °C) over thermally stable C (C> 400 °C). This was highlighted by high R400 in all land uses, (0.73-0.82). Carbon composition results indicated dominance of O-alkyl C in all land-use types. This was consistent with dominance of low-thermally stable C and a High R400 index. Overall, findings show that both wetland conversion and hydrological conditions strongly influenced OM quality and stability in the Yala wetland.
How to cite: Owino, C., Ngatia, L., Kitaka, N., Kipkemboi, J., Ondiek, R., Bugna, G., and Holmes, S.: Effects of Land-Use Change and Hydrology on Soil Carbon Composition and Thermal Stability in a Tropical Freshwater Wetland: Insights from Yala, Kenya, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8176, https://doi.org/10.5194/egusphere-egu26-8176, 2026.
Shallow lakes (89% of global lakes) face escalating pressures from eutrophication and climate change, yet comprehensive monitoring of chlorophyll-a (Chl-a) spatiotemporal dynamics remains challenging due to high costs and logistical constraints of traditional sampling. Developing transferable satellite-based frameworks is essential for scaling lake management from individual systems to regional assessments, particularly as climate warming intensifies phytoplankton bloom dynamics globally.
We developed an integrated remote sensing framework using four decades (1984-2023) of Landsat observations (30 m Chl-a). The framework integrates: machine learning-validated retrieval algorithms, exponential modelling for nutrient-driven spatial patterns, statistical phenological analysis, and zone-specific (littoral vs. pelagic) dynamics quantification. Trend detection employs Mann-Kendall tests with Sen's slope and bootstrap uncertainty estimates. Analysis of Lake Balaton (Central Europe, 596 km², 3.7 m depth) revealed: (1) robust exponential Chl-a decay from the primary nutrient source (k=0.04-0.06 km⁻¹) consistent across four decades and varying trophic conditions; (2) pronounced spatial heterogeneity with littoral zones maintaining 1.3-2.8× higher Chl-a than pelagic zones due to integrated signals from phytoplankton, benthic algae, and macrophytes; (3) climate-driven phenological advancement of 20 days in peak timing and 10 days in growing season onset, coupled with 0.7°C/decade surface warming; (4) 68% algal biomass reduction following nutrient management, demonstrating effective restoration despite concurrent climate pressures. The methodology is currently being extending to Lake Taihu (China, 2,338 km², 1.9 m depth) through international collaboration, testing framework performance across contrasting geographic, climatic, and trophic contexts. We will present comparative results examining the generalizability of spatial decay parameters, littoral-pelagic ratios, phenological response patterns, and climate sensitivity across these systems.
The transferable principles enable scaling from intensive single-lake studies to regional assessments, supporting evidence-based management for thousands of shallow lakes globally facing dual pressures of eutrophication and climate change.
How to cite: li, H., Somogyi, B., Tóth, V. R., Duan, H., Luo, J., and Woolway, R. I.: PanLake: A Transferable Framework for Monitoring Trophic Dynamics in Shallow Lakes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13554, https://doi.org/10.5194/egusphere-egu26-13554, 2026.
Climate change is amplified in the Arctic, which is warming four times faster than the globe. Lakes are abundant across Arctic landscapes, integral to hydrological cycles and associated ecosystem functions and services, and act as sentinels of environmental change in the region.
Across the terrestrial Arctic, widespread but spatially heterogeneous greening trends have been documented through remote sensing, linked to field-observed increases in vegetation growth, range expansion, and altered community composition. Concurrently, increases in terrestrial organic matter loading have been reported in some Arctic lakes, associated with browning, while other lakes are greening, linked to enhanced algal growth under shifting nutrient and thermal conditions.
While the theoretical basis for recent catchment vegetation and lake-water quality shifts is clear, circum-Arctic evidence linking the two phenomena remains scarce.
Here, we assess coupled greening and browning trends of terrestrial vegetation and aquatic indicators (total organic carbon, TOC; chlorophyll-a, ChlA) in ~100 circum-Arctic lake-catchment systems across Alaska, Canada, Greenland, Fennoscandia, and Russia. TOC and ChlA are reconstructed from sediment records using visible–near infrared spectroscopy (VNIRS)-based inference. Catchment vegetation change is quantified based on annual peak greenness and growing-season length, using spectral vegetation indices (NDVI, EVI2, and NIRv) from Landsat, AVHRR, and MODIS satellites over 1984–2025. Patterns in vegetation trends are described and analyzed using a custom land-cover reclassification, aboveground biomass, and vegetation height datasets.
Our remote-sensing results indicate widespread greening of catchments since the 1980s, at heterogeneous rates across Arctic regions and vegetation zones. Early sediment-based reconstructions indicate TOC increases in numerous lakes over the same period; ChlA is generally increasing but not consistently coupled to TOC. The greening-browning relationship will be evaluated through multivariate association analyses, accounting for physiographic and bioclimatic setting (e.g., latitude, topography, temperature/precipitation, vegetation type, hydrological connectivity). Our presentation will summarize catchment vegetation and lake-water TOC and ChlA trajectories across the Arctic, and identify the conditions under which they are linked most strongly.
How to cite: Strötz, L., Virtanen, T., Weckström, K., Heikkilä, M., and Weckström, J.: Browning Lakes in a Greening Arctic: A Sediment- and Satellite-Based Circum-Arctic Synthesis, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12055, https://doi.org/10.5194/egusphere-egu26-12055, 2026.
Evaporation is a key component of freshwater loss of lakes. Policy makers need reliable evaporation projection for adaptive allocation of water resources. However, large uncertainty exists in global lake evaporation rate (E) projection. When scenario is fixed, the uncertainty is mainly arisen from climate model uncertainty, that is the choice of Earth system model (ESM) outputs to drive lake model. However, the relative contribution of ESMs structural uncertainty is still unclear. Furthermore, there is no physics-informed method to reduce structural uncertainty. A primary reason is that multi-model ensemble projections of lake E in online mode are still absent. To address the shortcoming, we firstly combined Community Earth System Model 2 (CESM2), the only one with lake E projections under SSP370 in CMIP6, with automatic machine learning algorithm to establish a global lake E emulator. The emulator “solves” the lake E statistically with high efficiency instead of numerically. The dynamic interactions between lake and atmosphere are also preserved in the emulator by training with the CESM2 Large Ensemble (LENS2). The emulator can produce global online multi-model projections of lake E under SSP370 scenario with 30 ESM atmospheric forcing variables. Then, the structural uncertainty is calculated as standard deviation among multiple ESMs. At last, the emergent constraints for lake E structural uncertainty were established in different climate zones and at the global scale. The results show that structural uncertainty is the largest for tropical lakes. VPD is an optimal variable used for emergent constraints. After emergent constraints, Lake E in tropical climate will increase a little faster with reduced uncertainty (~23%). This study can provide theory support for enhancing credibility of future lake water storage projection, also show the direction for improving lake processes simulation in next generation of ESMs.
How to cite: Wang, W., Wen, Z., Zheng, Z., Oki, T., and Lee, X.: Reducing the structural uncertainty of global lake evaporation rate projection, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15390, https://doi.org/10.5194/egusphere-egu26-15390, 2026.
Harmful algal blooms (HABs) increasingly threaten freshwater ecosystems under intensifying anthropogenic and climatic pressures. Accurate short-term forecasting of HABs remains challenging, particularly in shallow lakes where phytoplankton dynamics are strongly influenced by meteorological variability through its effects on mixing intensity, thermal structure, and light availability. These rapid, non-stationary processes play a critical role in the development and decay of algal blooms, yet they remain poorly resolved by conventional low-frequency monitoring and are often oversimplified in predictive models relying on temporal persistence alone.
In this study, we investigate seasonal algal dynamics in Lake Taihu, a large shallow lake in China, using high-frequency vertical profiling data acquired by an autonomous monitoring system, providing a high-resolution dataset comprising 3 to 5 readings per second, and moving 2–3 cm per dataset, including observations of water temperature, conductivity, dissolved oxygen, pH, colored dissolved organic matter, chlorophyll-a, phycocyanin, and underwater photosynthetically active radiation, together with concurrent meteorological forcing including wind, air temperature, atmospheric pressure, and precipitation. This unique combination enables the explicit characterization of diel to seasonal variability in vertical water-column structure under changing meteorological conditions.
To extract spatiotemporal patterns from these heterogeneous observations, we apply a hybrid deep learning framework that integrates convolutional, recurrent, and attention-based components to predict short-term vertical chlorophyll-a dynamics. Rather than relying purely on autoregressive persistence of biomass, the process-guided model (Phytoformer) is designed to learn the influence of physical drivers associated with wind-driven mixing, stratification, and light attenuation, thereby enhancing ecological interpretability and physical consistency. High short-term predictive skill based on biomass persistence does not necessarily imply an understanding of the environmental drivers that govern bloom intensification or decay. Feature relevance analyses further indicate that physical controls modulate phytoplankton dynamics beyond short-term state persistence, with distinct seasonal patterns.
Our work demonstrates the potential of integrating high-resolution vertical sensing with interpretable deep learning to improve short-term prediction and early warning of HABs across seasons. Ongoing work extends this hybrid modeling framework to deep stratified Wahnbach Reservoir in Germany, where HABs can bloom in specific depth layers under contrasting water quality regimes. This cross-system application aims to explore model generalizability and to identify how dominant physical drivers differ between shallow and deep lake environments.
How to cite: Wei, G. and Norra, S.: Short-term prediction of algal dynamics in freshwater under meteorological variability: insights from high-frequency vertical observations and hybrid modeling , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20947, https://doi.org/10.5194/egusphere-egu26-20947, 2026.
Inland waters in semi-arid regions respond rapidly to both climate variability and human pressure, but the mechanisms linking external forcing to groundwater–surface water connectivity are still poorly understood, particularly in tropical lakes. Maar lakes are specially well suited to explore these processes because they are directly embedded in regional groundwater flow systems. We examine these interactions in Lake Alchichica (central Mexico), a semi-arid maar lake that has undergone a persistent decline in water level over recent decades. We developed a conceptual model based on a multiproxy approach combining effective precipitation, regional hydrogeochemistry, isotopic and physicochemical lake data, and groundwater level dynamics. Hydrogeochemical and isotopic patterns indicate a tight coupling between regional groundwater flow and lake water, with progressive chemical evolution along the flow path and increasing ion concentrations driven by intense evaporation. Between 2017 and 2021, groundwater levels dropped by ~38 cm, pointing to a reduction in subsurface inflows and a direct impact on the lake water balance. This decline cannot be explained by meteorological variability alone and instead suggests system-scale changes, likely associated with regional groundwater exploitation and long-term climate variations. Although groundwater chemistry has remained relatively stable, reported shifts in lake temperature and composition indicate emerging pressures on ecosystem functioning. Together, these results show how climatic and anthropogenic forcing can reshape groundwater–lake connectivity threatening lake's habitat.
How to cite: Silva-Aguilera, R., Escolero, O., Alcocer, J., Morales-Casique, E., Olea-Olea, S., Vilaclara, G., Lozano-García, S., and Correa-Metrio, A.: Climate and human-driven shifts in groundwater–lake interactions in a semi-arid maar lake, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21681, https://doi.org/10.5194/egusphere-egu26-21681, 2026.
How to cite: Wang, W., Woolway, I., Shi, K., and Zhang, Y.: Chinese ice-lake line shifts under climate change, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8655, https://doi.org/10.5194/egusphere-egu26-8655, 2026.
The St Lawrence River and the Laurentian Great Lakes form one of the longest deep draft navigation systems in the world. However, this golden inland waterway is typically closed during winter due to ice cover on the river and lakes. As the Great Lakes basin is projected to become warmer and less ice-covered, climate warming is expected to stimulate new opportunities for winter shipping activities in this region.
This study analyses the projected ice data in the Great Lakes basin over the 21st century from a two-way coupled climate-lake model (GLARM-v2). We proposed a safe navigation criterion for winter shipping in the lakes based on projected ice conditions, saying ice coverage smaller than 0.7~0.8 and ice thickness smaller than 15 cm. With this criterion, we found that under the high-emissions Representative Concentration Pathway (RCP) 8.5 scenario, 68% of the Great Lakes region is projected to be navigable year-round by late-century (2080–2099).
Based on historical real-world shipping activity records, we identified 65 established navigation routes in this region. Under RCP 8.5, the annual ice-blocked duration for these navigation routes is projected to shorten by 78% by late-century (2080–2099) relative to the historical baseline (2000–2019), which means a two-month extension of annual shipping season. These changes have the potential to shift winter cargo transportation from land-based modes like railway and heavy truck to the shipping industry. Such a shift can potentially save billions in transportation costs and reduce substantial greenhouse gas emissions from the transport sector.
How to cite: Shi, H., Xue, P., Liu, M., Huang, C., Kayastha, M. B., Sharma, S., Yang, H., Wang, W., Long, D., Feng, L., Liu, Y., Wong, C. W. Y., Lai, K., and Woolway, R. I.: Future winter shipping opportunities in the Great Lakes–St. Lawrence Seaway, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8957, https://doi.org/10.5194/egusphere-egu26-8957, 2026.
Lake ecosystems are increasingly exposed to multiple stressors arising from the combined effects of climate change and human activities, leading to a range of lake health issues, including oxygen depletion, eutrophication, algal blooms, and even regime shifts. These interacting stressors complicate the diagnosis of lake health and underscore the need for integrative, process-based approaches that explicitly link physical and biogeochemical processes. In this study, we apply a process-based lake ecosystem model (GOTM-WET) to assess and project the ecosystem health of Windermere (South Basin) in the Lake District National Park, UK, a deep, dimictic lake with extensive long-term observations. The model integrates meteorological forcing with in situ measurements of water temperature and dissolved oxygen (DO) to explicitly resolve physical mixing, thermal stratification, and biogeochemical oxygen dynamics. Model calibration is conducted in a stepwise and hierarchical manner, first constraining physical processes and subsequently ecosystem processes, thereby ensuring a robust representation of the coupled physical–biogeochemical lake system. Using the well-calibrated model, we derive a suite of process-based lake health indicators that capture both physical and ecological dimensions of lake functioning. These include stratification characteristics, vertical mixing efficiency, and seasonal hypolimnetic DO depletion rates, which together reflect the capacity of the lake to sustain oxygenated habitats and maintain resilient biogeochemical cycles. Model results demonstrate that variations in physical mixing regimes exert a dominant control on deep-water oxygen dynamics, with important implications for ecosystem stability and habitat quality. By linking observable lake health indicators to underlying ecosystem processes, this study demonstrates the value of process-based modelling for comprehensive lake health assessment. Unlike purely empirical or index-based approaches, the GOTM–WET enables scenario-based simulations and mechanistic interpretation, providing a powerful tool for evaluating lake ecosystem responses under multiple stressors. The approach and evaluation framework developed here is transferable to other lake systems and offers a foundation for scaling lake health assessments from individual lakes to broader regional applications.
How to cite: Xue, Y., Mackay, E., Kong, X., Zhang, Y., and Woolway, I.: Assessing and projecting lake health in a changing world using a coupled physical–biogeochemical model: a case study of Windermere, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-23248, https://doi.org/10.5194/egusphere-egu26-23248, 2026.
Metabolism is an essential component of carbon cycling in river ecosystems, and understanding its response to climate change on a broad scale is imperative. Here we employ deep-learning models trained on an extensive data set to reconstruct daily metabolism in a total of 293 rivers and streams across the continental US from 1980 to 2020. Three key variables, gross primary production (GPP), ecosystem respiration (ER), and net ecosystem production (NEP), are examined to unveil longterm trends. Our analysis reveals that continental US rivers and streams experience an increase of 0.045 g O2 m−2 day−1 decade−1 in GPP from 1980 to 2020, largely driven by alterations in runoff and insolation, while ER declines more strongly at a rate of 0.078 g O2 m−2 day−1 decade−1 , primarily attributed to the combined effects of discharge, thermal conditions, and temperature changes. Such changes have caused a slight decrease in the NEP over the past four decades. Moreover, our well-trained models project that NEP continues to decline at a rate of 0.017 ± 0.008 g O2 m−2 day−1 decade−1 under future climate scenarios, resulting from asymmetric and converse trends between GPP and ER. Such persistent net heterotrophy shifts would threaten aquatic biodiversity and weaken ecological resilience of ffowing waters to climate change.
How to cite: Guan, Q., Shi, K., Woolway, R. I., Qin, B., Zhang, Y., and Ran, L.: Declining Predictions of Net Ecosystem Production in US Rivers and Streams Throughout the 21st Century, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12035, https://doi.org/10.5194/egusphere-egu26-12035, 2026.
Lake Hovsgol in Mongolia is a large deep mountainous lake. This lake is located in continental climate conditions and is ice-covered every year between December and June. In winter large water volume lead to significant heat inertia, late ice cover formation and strong temperature contrast between air over the lake and over land.
We first discuss a mesoscale cyclone that has been formed over the lake in December 2023. There are extratropical mesoscale cyclones which take their energy from the large-scale baroclinic instability, such as most cyclones in the Mediterranean sea. However, some cyclones such as Medicanes (“Mediterranean hurricanes”) and polar lows develop from both baroclinic instability (like extratropical cyclones) and surface exchanges over the relatively warm sea (like tropical cyclones). There were also cases when cyclones were observed over lakes, such as Great Lakes, or Lake Victoria, but in most cases these cyclones developed elsewhere and their size was several hundreds of kilometers - much larger than the lakes themselves.
We analyse the generation, evolution and dissipation of a cyclone over lake Hovsgol in 2023 using various satellite imagery in the visible, thermal and microwave ranges, as well as meteorological data. Rapid decrease of air temperature from –8 to –30°C led to wind oriented from the coast to the lake, creation of several convergence lines and ultimately formation of a cyclone with outer radius of about 35 km. This cyclone has been generated over the lake itself (and not advected from some other regions) and its size was limited by the lake size which itself is 130x35 km. The cyclone was short lived (about 24 hours) but had a well-developed cloud-free eye with diameter of 3.5 km, comma head and outflow cirrus shield. Heavy snowfall was observed at that time by local populations. Two days after cyclone dissipation most of the lake was ice covered.
We present data on cyclone position and displacement, estimate speed and direction of wind-driven ice drift during the cyclone presence and based on this assess potential speed of surface wind. We also estimate height and temperature of cloud cover. We discuss the potential structure of the cyclone, its influence on surface water currents and ice formation.
We also present several other cases when such cyclones have been observed over lake Hovsgol in other years. These examples confirm that such events are a repeatable feature over deep and large lakes, and we propose to call them Limnocanes (by analogy with Medicanes).
This research was supported by the CNES TOSCA LAKEDDIES-II, TRISHNA and SWIRL projects. A.G. Kostianoy was supported in the framework of the Shirshov Institute of Oceanology RAS budgetary financing (Project N FMWE--2024-0016).
How to cite: Kouraev, A. V., Pantillon, F., Maury, N., Zakharova, E., Kostianoy, A., Hall, N., Marchesiello, P., and Suknev, A.: Land-water-atmosphere interaction over a deep large high-altitude lake: generation of mesoscale cyclones (limnocanes) over Lake Hovsgol (Mongolia), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12751, https://doi.org/10.5194/egusphere-egu26-12751, 2026.
Comprehensive long-term insights into lake thermal dynamics—spanning both historical evolution and future trajectories—are critical for assessing climate change impacts on freshwater ecosystems. Unlike gridded surface temperature products that average over land and water, lake-specific datasets like GLAST offer superior precision by resolving thermal dynamics for 92,245 individual lakes worldwide. However, the previous version (v1.0, https://zenodo.org/records/8322038) was constrained by a historical record ending in 2020 and reliance on older CMIP5-based forcing. Here, we introduce GLAST v2.0, which overcomes these limitations by extending the historical reconstruction and integrating latest-generation projections. Using the FLake model calibrated against satellite observations, we extended historical simulations (driven by ERA5-Land) to 1981–2025, thereby capturing recent extreme warming events. Future projections (2015–2100) were upgraded to the ISIMIP3b (CMIP6) protocol under SSP1-2.6, SSP3-7.0, and SSP5-8.5 scenarios. Acknowledging the inherent differences between reanalysis and ESM forcing, we intentionally retain the 2015–2025 overlap period to allow users to quantify discontinuities and apply tailored bias corrections. Extensive validation against independent observations confirms the dataset's robust performance in capturing interannual variability and recent warming trends. GLAST v2.0 provides a vital, high-resolution resource for assessing lake thermal evolution under the latest climate narratives.
How to cite: Tong, Y., Feng, L., and Woolway, R. I.: GLAST v2.0: A lake-specific daily surface water temperature dataset (1981–2100) integrating recent extremes and CMIP6 projections, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16744, https://doi.org/10.5194/egusphere-egu26-16744, 2026.
Northern regions are experiencing warming rates that significantly exceed the global average, triggering rapid and profound changes in freshwater ice dynamics. These changes manifest as delayed freeze-up, earlier break-up, and, critically, a reduction in ice thickness that threatens the safety of traditional travel routes. Addressing the scarcity of lake-specific ice thickness data in northern communities, this study employs the FLake numerical model to estimate ice thickness variations from 1981 to 2025 for 161 lakes identified along community winter travel routes. By integrating these simulations with safety thresholds derived from local community surveys, we quantify the reduction in days of safe access. Results indicate a significant thinning trend, with annual mean and maximum ice thickness decreasing at rates of 1.42 cm/decade and 1.43 cm/decade, respectively. Consequently, the duration of safe access has declined by a cumulative total of 11.8 days over the 45-year period (a rate of 2.67 days/decade). This study elucidates how accelerated regional warming is compromising essential winter mobility, providing a scientific basis for developing adaptation strategies to mitigate risks for ice-dependent communities across northern latitudes.
How to cite: Shan, J., Tong, Y., Woolway, R. I., Malik, I. H., and Ford, J. D.: Declining lake ice thickness and its implications for community travel in northern regions: a modeling study (1981–2025) , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17949, https://doi.org/10.5194/egusphere-egu26-17949, 2026.
Reservoirs are increasingly recognised as dynamic components of the global carbon cycle. Yet, their greenhouse gas (GHG) emissions are still poorly understood due to strong spatiotemporal variations, seasonality and the scarcity of in-situ measurements. Climate-driven variability in thermal conditions, hydrodynamics and reservoir morphology is expected to control both the magnitude and temporal variability of carbon dioxide (CO₂) as well as methane (CH₄) emissions. However, these controls remain poorly understood at the global scale.
Here, we combine satellite observations and machine-learning models to examine climate-related patterns in reservoir GHG emissions across more than 21,000 reservoirs globally from 2020 to 2024. Average CO₂ and CH₄ emissions on a monthly scale are obtained by combining GHG concentration-based observation from the Greenhouse Gases Observing Satellite (GOSAT) with climate reanalysis data (ERA5) and relevant reservoir information such as surface area or catchment area. We employ tree-based ensembles of models to estimate monthly emissions and explore how emissions vary with season, location and reservoir characteristics among different hydroclimatic regions.
The resulting emission estimates exhibit clear global seasonal variations and show a strong seasonal phasing, with most emissions peaking during local seasonal extremes. Seasonal emissions show less variation in larger reservoirs while the smaller reservoirs show greater seasonal changes because they are strongly influenced by climate forcing and have less ability to moderate variability. Spatial aggregation reveals strong zonal differences and nonlinear relationships with thermal regimes, highlighting the complex interplay between climate variability and physical characteristics of the reservoir on GHG emissions regulation.
Together, these findings show that machine learning models using satellite-derived information can reveal physically consistent spatiotemporal patterns in reservoir GHG emissions at global scales. While comprehensive site-scale validation remains limited at the global scale, the observed consistency across temporal, spatial and physical characteristics reconfirms that satellite-enabled modelling could be useful to assess climate-driven variability in inland-water carbon emissions at larger scales and guide focused future observational efforts.
How to cite: Seth, M., Ubierna Aparicio, M., Diez Santos, C., and Outram, F.: Climate-driven controls on greenhouse gas emissions from global reservoirs inferred from satellite observations and machine learning, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19072, https://doi.org/10.5194/egusphere-egu26-19072, 2026.
The Harz Mountains, situated in the north of Germany, are about 120 km long and about 40 km wide. Their highest mountain is Mount Brocken (1,141 m a.s.l.). The mountain range is known for ancient silver and base metal mining. Today the Harz Mountains are an important drinking water supply region for northern Germany.
About 70 lakes are situated around the town of Clausthal-Zellerfeld in the Western Harz Mountains. These lakes were constructed to save a continuous water supply to the ore mines about 200 – 500 years ago. The water depths range from about 3 to 15 m, the storage volume from about 10,000 to 600,000 m3. The lakes are an important part of the UNESCO World Heritage Site "Oberharzer Wasserregal". Most of the lakes are oligotrophic with pH values of about 7 and SEC values below 200 µS/cm (Bozau et al., 2015). Some of the lakes are used for the drinking water supply of nearby communities and are still important for the protection of floods.
From 2023 – 2025, the water column of selected mine lakes was investigated. Samples of the water column were analysed for major ions, trace metals and stable isotopes. In summer, the formation of a deep anoxic layer (hypolimnion) was observed in some lakes. The intensity of anoxic conditions depends on the summer temperatures, precipitation rates and wind conditions. There is a typical chemical stratification of the water column for every single lake. Shallow lakes showed stronger redox reactions than deeper lakes. Colder weather periods with high precipitation rates during the summer time can minimise the extent of the hypolimnion. SEC, bicarbonate, Fe and Mn are enriched in the anoxic layer leading to problems in the traditional treatment of drinking water. Nitrate and sulphate are depleted due the chemical reactions under anoxic conditions. The ratio Mn/Fe proved to be a very sensitive indicator for the formation of the hypolimnion. The δ18O and δ2H values in the water column of mine lakes also reflect the seasonal stratification. Due to evaporation effects at the water surface the highest δ18O and δ2H changes are found in mine lakes during summer time. The δ13C values in the the water column range between -24 … -13 ‰. The lowest δ13C values are found in the anoxic hypolimnion during summer time. Due to warmer and longer spring, summer and autumn seasons the formation of hypolimnia increased in the last years and the treatment of drinking water was adapted.
Bozau E, Licha T, Stärk HJ, Strauch G, Voss I, Wiegand B, 2015. Hydrogeochemische Studien im Harzer Einzugsgebiet der Innerste. Clausthaler Geowissenschaften 10, 35-46.
How to cite: Bozau, E., Schäfer, T., and Licha, T.: Redox and carbon cycling in mine lakes of the Upper Harz Mountains (Germany), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-194, https://doi.org/10.5194/egusphere-egu26-194, 2026.
Suisun Marsh is the largest tidal wetland on the west coast of North America, existing at the interface of the Sacramento-San Joaquin (SSJ) Delta and the San Francisco Bay in California. This dynamic landscape acts as a model system for observing the impacts of environmental changes; as a result, long-term monitoring efforts have been consistently deemed as a priority to evaluate the efficacy of restoration projects. We analyze the trends in fishes and water quality variables in Suisun Marsh from 1995-2024, specifically honing in on the recovery of an obligate floodplain-spawning fish (Sacramento Splittail) and contextualize what may have influenced its increases in abundance. We use the Normalized Difference Water Index as a proxy for floodplain availability compared to abundance data within Suisun Marsh, collected monthly at 25 sites. We additionally delve into distributions of fishes in Suisun Marsh and where they occur spatially, with respect to environmental conditions. Water quality samples were taken at each of the sites alongside biotic surveys once a month, including salinity, dissolved oxygen, turbidity, depth, and temperature, which were additionally compared to calculations of Delta Outflow (a metric representing the approximate quantity of freshwater entering the system). We hypothesize that the recovery of Sacramento Splittail population was ‘unintended’ as a result of nearby restoration efforts to wetland habitat targeting a different species. Once listed as a threatened species, the increases in floodplain availability then seem to represent a marked growth in abundances of Splittail. Larger implications of this project includes the evaluation of the single-species management approach common in the USA as well as the implications for nonnative species management.
How to cite: Evans, K. and Durand, J.: Tidal Wetlands and Environmental Drivers in Species Recovery: Suisun Marsh, CA (USA), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6023, https://doi.org/10.5194/egusphere-egu26-6023, 2026.
High Andean vegas constitute ecologically and functionally critical wetlands, representing some of the most fragile ecosystems within the mountainous environments of the Andes. These systems sustain high levels of biological diversity and endemism, providing habitat for numerous plant and animal species that exhibit strong sensitivity to hydrological and climatic variability. In addition, they fulfill essential ecosystem functions, including regulation of water balance, provision of ecosystem services, and freshwater supply—upon which approximately 12.4 million people in central Chile depend.
A comprehensive understanding of the physical conditions that govern the synchronization of the snowpack in its solid and liquid phases—closely linked to the magnitude of seasonal water storage—and its interaction with periods of carbon sequestration is fundamental for interpreting the dominant processes that regulate the functioning of these ecosystems. To this end, we conducted extensive field measurements between 2023 and 2025, integrating data from automated weather stations (AWS) with gas exchange observations obtained through an IRGASON eddy covariance system. Furthermore, we calibrated and validated two physically based models, CRHM (Pomeroy et al., 2007) and LASSLOP (Lasslop et al., 2010), using unprecedented snow–hydrometeorological and gas exchange datasets from the Subtropical Andes of Chile. This approach enabled us to characterize CO₂ fluxes, water vapor exchange, and the dynamics of surface energy balance with high resolution and reliability.
The primary objective of this study is to elucidate the functioning of high Andean vegas, with particular emphasis on the energy fluxes that regulate carbon and water cycle mass balances and their linkages to biodiversity structure and dynamics. The results are intended to provide a robust scientific basis for evidencedriven management of these ecosystems and to inform the design of conservation and functional restoration strategies in the context of ongoing degradation and biodiversity loss.
Our analyses demonstrate that, under favorable hydrological conditions—characterized by sustained snowmelt inputs, subsurface inflows, and prolonged soil saturation—high Andean vegas operate predominantly as carbon sinks, with an estimated annual sequestration rate of −1.28 × 10-4 Ton Eq CO2 m-2. In addition, they store subsurface water volumes of up to 250 L s-1, with extended residence times that maintain streamflow during the dry season. Conversely, perturbations to the hydrological regime—including persistent groundwater declines associated with prolonged drought, diminished snow–glacial contributions, and increasing air and soil temperatures—combined with anthropogenic pressures such as overgrazing, vehicular traffic, soil compaction, and channelization for agricultural purposes, can trigger severe and potentially irreversible losses of ecosystem functionality. These impacts manifest as sharp declines in biodiversity and a net release of CO2 to the atmosphere.
This functional duality highlights the critical role of high Andean vegas in biodiversity conservation, climate change mitigation, and hydrological regulation within mountain basins. The balance between carbon sequestration and carbon emission is tightly coupled to hydrological status, vegetation condition, and the degree of ecosystem disturbance. In this context, timely, sciencebased management interventions are essential to mitigate biodiversity loss at local and regional scales, particularly given the role of these wetlands as strategic biological corridors across the Andes.
How to cite: Videla-Giering, Y., Novoa-Cortez, D., Ibaceta-Guerrero, P., Aravena-Perez, J., Lucero-Salazar, T., Rubilar-Donoso, J. P., Novoa-Cortez, F., and Contreras-Leiva, M.: Interaction of CO2 Fluxes in the Hydrological Dynamics of Mountain Basins in the Semiarid Andes – Central Chile, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11303, https://doi.org/10.5194/egusphere-egu26-11303, 2026.
