Hydrological drivers dictate the spatial structure and connectivity of catchment areas, with cascading effects on riverine ecosystems (e.g., transport of nutrients and organic resources, organism dispersal), whereas ecological communities affect regional hydrology (e.g., through transpiration, ecosystem engineering) and regulate the biological and geochemical cycling of elements in water (e.g., carbon, nutrients, metals, pollutants).
This session aims to foster exchange of novel findings from interdisciplinary research on the interplay of hydrological, biogeochemical and ecological processes in watersheds and riverine systems. We welcome studies on (but are not limited to):
● Ecohydrological dynamics, riverine metacommunities, and food webs;
● Carbon and nutrient cycling, elemental fluxes across rivers, soils, and lakes, eutrophication, and stream metabolism;
● Biogeochemical processes in high-mountain catchments examined through integrated terrestrial-aquatic-atmosphere perspectives;
● Effects of anthropogenic interventions, land use and climate change on interactions among these processes;
● Representation of anthropogenic forcing alongside hydrological, biogeochemical, and ecological processes in ecohydrological models, including translation of experimental knowledge into watershed-scale frameworks, advances in model structures and parametrization schemes, coupling across modelling systems, and robust model evaluation strategies.
We seek contributions that employ a range of theoretical methods, monitoring techniques (e.g., in-situ, remote sensing), and/or modelling approaches (e.g., statistical, process-based, machine/deep-learning-based) at diverse spatial scales from reach and plot scale, to single watersheds and streams, and entire river networks.
We are particularly interested in contributions where tools and methods from one discipline are used to generate insights in another. By bringing together scientists from diverse disciplines, this session seeks to foster interdisciplinary dialogue and collaboration on hydrological, biogeochemical and ecological research.
Orals: Fri, 8 May, 08:30–12:30 | Room 3.16/17
Mountain lakes are vulnerable to global change; particularly the dual threat of climatic warming and atmospheric deposition. These changes can increase greenhouse gas (GHG) emissions, and lead to the accumulation of emerging contaminants such as toxic nanoplastics. In Sweden, the majority of lake GHG research has been on lakes within forest and mire environments, and nanoplastics have only been measured in one lowland catchment. Thus, the biogeochemistry of mountain lakes remains largely an unknown. Here, we report the results of a summer sampling campaign from two mountain regions in Central Sweden: Fulufjället and Jämtland. The regions face different pressures; in Jämtland, reindeer grazing is widespread whilst Fulufjället is ungrazed but closer to central European urban areas, which are a plausible source of long-range dispersal of nanoplastics. Within each region we sampled 16 mountain lakes and 4 lower altitude forest lakes as comparators. We measured dissolved GHGs (CH4, CO2, N2O), carbon isotopes (δ13C-CH4 δ13C-CO2), nanoplastics, DOM composition (via fluorescence) and reactivity, extracellular enzymes and an array of water chemistry (including organic and inorganic C, N, P).
Preliminary findings show the presence of nanoplastics (polymers PE, PP, and PET), low concentrations of inorganic N and P, low DOM reactivity, and relatively low concentrations of CH4 and N2O in mountain lakes. Here, we present more detailed analyses, including comparisons between mountain and forest lakes, and between the two regions. Together, our data provide the first integrated assessment of GHGs, nanoplastics, and biogeochemistry in Swedish mountain lakes; and, to our knowledge, the first such study globally. This “health check” highlights the vulnerability of mountain lakes to ongoing environmental change and provides a baseline by which to monitor future anthropogenic changes.
How to cite: Peacock, M., Aberg, D., Bass, A., Davidson, S., Dickinson, S., Heffernan, L., Kothawala, D., Materić, D., Wallin, M., and Futter, M.: A health check of Swedish mountain lakes: greenhouse gases, nanoplastics, enzymes and water chemistry, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-444, https://doi.org/10.5194/egusphere-egu26-444, 2026.
How to cite: Huang, L., Hu, Z., Yang, H., Wu, X., Lu, H., and Zhu, L.: Seasonal Variability of CO2 Exchange in a High-Altitude, Freshwater Lake on the Tibetan Plateau: Insights from Eddy Covariance-based Observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21111, https://doi.org/10.5194/egusphere-egu26-21111, 2026.
Many mountain watersheds in the Rocky Mountains in Colorado, USA, are impacted by natural acid rock drainage (ARD) and acid mine drainage (AMD), which mobilize trace metals and rare earth elements (REEs) into surface waters. Analysis of long-term water quality records for alpine tributaries receiving ARD in the Colorado Mineral Belt indicates that warmer summer conditions have been driving increases in the concentrations of sulfate, trace metals and rare earth elements (REEs). One example of these climate-change impacts is the Lincoln Creek Watershed, where a highly mineralized tributary contributes a substantial ARD loading into the headwaters, with an additional AMD contribution from a nearby abandoned mine, the Ruby Mine. We evaluated the transport, mixing, and attenuation of major solutes, trace metals and REEs across the snowmelt to fall period. Water samples from six main sites along a 7-km reach of Lincoln Creek below the ARD and AMD inflows were analyzed by Inductively-Coupled Plasma Mass Spectrometry (ICP-MS) and Ion Chromatography (IC) methods. The results were explored through transport calculations employing sulfate as a conservative natural tracer. Water chemistry in Lincoln Creek reveals distinct geochemical fingerprints for the Ruby Mine (enriched in Ca, Mg, Mn, and Cd) and the Mineralized Tributary (enriched in SO4, Fe, Al, and Cu). REE fractionation patterns and Ce anomalies further distinguish source contributions and processes, with the Mineralized Tributary displaying MREE enrichment from natural pyrite weathering and the Ruby Mine exhibiting HREE enrichment tied to mine derived flows. Most solutes exhibited conservative transport during mid-summer when the pH values were low, in the range of pH 4-4.5. During the higher flows associated with snowmelt instream losses of some trace metals and REEs was observed, which was also the case in the fall. These results indicate that both source composition, instream pH-dependent reactivity and hydrologic processes interact to control the downstream water quality impacts associated with these high mountain sources of ARD and AMD.
How to cite: McKnight, D., Marchitto, T., Bolin, A., and Odorosio, A.: Acceleration of Weathering of Trace Metals and Rare Earth Elements in Alpine Watersheds in the Colorado Mineral Belt, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16752, https://doi.org/10.5194/egusphere-egu26-16752, 2026.
Rapid warming in polar and alpine regions is accelerating glacier retreat, producing vast quantities of meltwater and sediments that are delivered to downstream ecosystems. Glacial meltwaters contain essential micronutrients, such as iron (Fe) and manganese (Mn), which may stimulate primary production in freshwater and marine ecosystems, potentially influencing carbon cycling. While dissolved Fe and Mn cycling are relatively well studied, the role of sediment-bound species remains poorly constrained despite their high potential bioavailability.
Here we present data on sediment-bound and dissolved Fe and Mn concentrations and flux, and associated chemical weathering processes, along source-to-sink transects in glacierized catchments of the High Arctic (Svalbard Archipelago) and Sub-Arctic regions (Jostedalsbreen ice cap and Jotunheimen mountain range, Norway). We analyzed meltwaters from 20 glacierized catchments spanning diverse lithologies with glacial coverage ranging from 3% to 62%, including metamorphic, sedimentary, carbonate, and plutonic substrates. Dissolved trace elements (<0.45 μm) were measured using ICP-MS/MS, while sediment-bound fractions were extracted with ascorbic acid (labile phases) and dithionite (crystalline phases) and analysed by ICP-OES.
Our results reveal striking contrasts between regions. Svalbard glacial streams exhibited sediment-bound Fe and Mn concentrations at least one order of magnitude higher than dissolved concentrations, whereas Norwegian glacial streams showed only few-fold higher particulate Fe relative to dissolved. Conversely, dissolved Fe was up to three times higher in Norwegian streams compared to Svalbard, whereas dissolved Mn was lower. Suspended particulate matter concentrations were also markedly different, with Svalbard streams showing concentrations near an order of magnitude higher than Norwegian streams.
Major ion chemistry indicates contrasting geochemical weathering processes. Major ion concentrations were generally higher in High Arctic streams compared to Sub-Arctic streams. Additionally, pH values were typically neutral to slightly alkaline in the High Arctic, while streams in Sub-Arctic catchments were more acidic. These patterns suggest regional differences in chemical weathering rate, buffering capacity, and glacio-fluvial erosion rates between regions. Stronger glacier recession and thinning, and biological expansion in proglacial zones of Norwegian glaciers compared to Svalbard may further contribute to these differences.
Our findings underscore the importance of sediment-bound element export and association with chemical weathering signatures and highlight regional differences in biogeochemical pathways during deglaciation. These insights are critical for predicting nutrient delivery to aquatic ecosystems in a warming world from glacierized regions.
How to cite: Stachnik, L., Telążka, M., Hawkings, J., Yde, J. C., Murphy, J. G., Raczyk, H., Łopuch, M., Proch, A., Proch, J., and Niedzielski, P.: Contrasting Export of Iron and Manganese between High Arctic and Sub-Arctic Glacierized Watersheds, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20867, https://doi.org/10.5194/egusphere-egu26-20867, 2026.
Photovoltaic (PV) power generation has attracted significant attention not only for its substantial carbon reduction potential but also as an emerging research focus regarding its ecological impacts, particularly in arid and semi-arid regions. The extensive construction of utility-scale PV plants on the desert areas alters near-surface microclimates, exerting non-negligible influences on ecosystems. While utility-scale PV plants significantly alter near-surface microclimates, traditional models often fail to capture the intricate feedback mechanisms between PV panels and the underlying surface. To address this gap, this study developed a novel ecohydrological model that explicitly integrates a physically-based PV canopy module into an existing ecohydrological model. Unlike conventional approaches, this model treats PV panels as a distinct canopy layer, allowing for the simultaneous resolution of energy and hydrological fluxes across the panel, vegetation, and soil interfaces. Validated at the Kubuqi PV power plant, located in the arid region of Northern China, the model demonstrated satisfactory performance. Results reveal significant ecological benefits at the Kubuqi PV power plant: gross primary productivity (GPP) increased by 110 gC·m-2 during the growing season compared to the natural scenario, accompanied by a carbon sink enhancement of 58 gC·m-2. This improvement is primarily attributed to a marked increase in water use efficiency (rising from 0.55 gC·m-2·mm-1 in the natural scenario to 1.12 gC·m-2·mm-1 in the PV scenario). Crucially, while the inter-panel areas functioned as a net annual carbon sink, areas directly under the panels acted as a carbon source. Although vegetation growth under the panels was suppressed by hydrothermal constraints, it exhibited higher water use efficiency, indicating enhanced resource utilization under limiting conditions. This research advances the understanding of PV effects on ecohydrological processes in arid and semi-arid areas and establishes a novel modeling framework integrating PV canopy influences for arid ecosystems.
How to cite: Cong, Z., Zhang, Z., Huang, Y., Li, S., Lei, H., and Yang, D.: Ecohydrological effects of photovoltaic plants in Kubuqi Desert based on ecohydrological modeling and field observation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9864, https://doi.org/10.5194/egusphere-egu26-9864, 2026.
Stratification strongly influences lake circulation, oxygenation, and biogeochemical exchange. In stably stratified lakes, deep and surface waters can differ markedly in chemical composition. Changes in mixing intensity or overturn events can therefore alter oxygen levels and water quality by redistributing reduced or nutrient-rich deep water.
Accurate modelling of circulation and air-water oxygen exchange in deep, low-salinity lakes requires thermobaric effects, i.e. the pressure-temperature dependence of water density. In such systems, density differences at depth can be small enough that thermobaricity becomes a primary driver of vertical exchange and renewal.
We investigate thermobaricity-driven circulation in a simplified setting using a 2D Boussinesq Navier-Stokes framework in which the buoyancy term is derived from the approximate equation of state for freshwater by Farmer and Carmack (1981). To assess deep water renewal and stratification persistence, we introduce a passive “water age” tracer. We first compute a time-periodic solution for the flow and temperature fields, and then transport the age tracer over many cycles using this periodic state. This approach enables efficient long-term estimates of water renewal time scales and their sensitivity to thermobaric forcing, providing a simplified assessment of physical stability in deep-lake stratification.
How to cite: Irmscher, J. and Richter, T.: A simplified 2D model for thermobaricity-driven circulation and water renewal in deep, low-salinity lakes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12521, https://doi.org/10.5194/egusphere-egu26-12521, 2026.
The ecological integrity of riverine ecosystems in semi-arid areas is largely affected by variations in the natural flow regime as these flows are increasingly disturbed by anthropogenic activities, particularly the construction of dams, diversion weirs and storage structures. The current study examines the basins of the Malaprabha and Ghataprabha rivers, which are two primary tributaries of the Krishna River in southern India. The water management in these rivers is significantly influenced by the Hidkal and Navilatirtha dams, which serve as large reservoirs for storage. The study's goal is to delve beyond the antiquated concept of "minimum flow" and to develop a comprehensive assessment of Environmental Flow (EF) requirements based on long-term data trends.
The methodology adopted a comprehensive trend analysis of hydrological and ecological data collected from multiple gauging stations, namely, Bagalkot, Gokak Falls, Cholachaguda, Mudhol, and Navalgund. The daily discharge data from the Central Water Commission (CWC) and Water Resources Department (WRD) of Karnataka are analysed using the Mann-Kendall test and Sen’s slope estimator for monotonic shifts in flow patterns. To measure the extent of the changes, the study applied the Indicators of Hydrologic Alteration (IHA) and the Range of Variability Approach (RVA) for determining 33 ecologically relevant parameters, including the magnitude, frequency, and duration of flow events.
To understand the notable differences between pre-dam (natural) and post-dam (controlled) situations, a preliminary assessment of the hydrological data is being carried out. These patterns are expected to show a significant dampening of natural flow frequency and magnitude, enabling the data-driven basis required to precisely forecast EF thresholds for the basins.
The study highlights the need to integrate hydrological data from multiple stations to understand the cumulative effects of interventions at the basin level. The study establishes the thresholds necessary to support native aquatic species and maintain the overall ecological health of these river systems by identifying variations in flow magnitude, frequency, and duration.
Keywords: Environmental Flows, IHA/RVA, Mann-Kendall Trend Analysis, Hydrological Alteration, Multi-station Analysis.
How to cite: Patil, R., Kv, J., and Desai, V. R.: Multi-Station Trend Analysis for Assessing Hydrological Alterations and Environmental Flow Requirements in the Malaprabha and Ghataprabha River Basins, India, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16502, https://doi.org/10.5194/egusphere-egu26-16502, 2026.
Hydrological models are widely used for water resources planning and management under changing environmental conditions. Therefore, it is important to assess the capability of these models to capture non-stationarity arising from climate variability and land-use change. The primary objective of this study is to evaluate the ability of the Soil and Water Assessment Tool (SWAT+) model to capture hydrological non-stationarities in the rainfall–runoff (r–r) mechanism caused by long-term fluctuations in precipitation, temperature, and Land Use/Land Cover (LULC) in Sugar Creek at Milford, Illinois (IL), USA. The analysis begins with the identification and characterization of non-stationarities in long-term hydroclimatic variables (1951–2020) using statistical change-point detection techniques. Temporal variations in the r–r relationship are examined using Analysis of Covariance (ANCOVA), which provides a formal statistical framework to test the linear dependence of the r–r mechanism on its driving variables. However, as hydrological responses are often nonlinear and governed by interacting drivers, ANCOVA alone is insufficient to fully explain how the relative influence of multiple dynamic variables evolves over time. To address this limitation, a machine-learning-based SHAP (Shapley Additive Explanations) analysis is employed to quantify the time-varying contributions of precipitation, temperature, and LULC fractions to streamflow observation, enabling an interpretable decomposition of the changing drivers. Complementing these data-driven analyses, SWAT+ simulations under dynamically varying climate and LULC conditions are analyzed to evaluate the model’s ability to capture hydrological non-stationarity. To examine model structural sensitivity, controlled perturbations of precipitation (±20%), temperature, and LULC are applied, and the resulting changes in major hydrological components are quantified using precipitation elasticity, temperature sensitivity, and LULC sensitivity indices. These diagnostics reveal shifts in process dominance—such as infiltration, percolation, evapotranspiration, and streamflow generation—under altered climatic and land-use regimes. Model calibration is conducted separately for pre-change and post-change periods to assess whether SWAT+ maintains parameter stability across different hydroclimatic states. Variations in optimal parameter values across climate and LULC scenarios are analyzed to quantify parameter uncertainty under non-stationary conditions. Overall, the results reveal substantial temporal variability in parameter sensitivity and demonstrate that fluctuations in precipitation, temperature, and LULC induce nonlinear hydrological responses that challenge the stationarity assumptions embedded in the SWAT+ model structure. The findings underscore the need for dynamic parameterization strategies to more accurately represent evolving watershed processes under changing climate and land-surface conditions.
How to cite: Sreenivas, S., Athira, P., and Kiesel, J.: Hydrological Non-stationarity in SWAT+ model Simulations under Changing Climate and Land Use Cover, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22388, https://doi.org/10.5194/egusphere-egu26-22388, 2026.
Fog is an important yet often-overlooked non-rainfall water source for many coastal, mountainous, and arid-to-semi-arid regions worldwide. From the limited ecological and agricultural studies conducted to date, we know that fog is particularly beneficial for plants during dry spells. Specifically, fog events support plant hydration and growth via foliar water uptake, enhance water- and light-use efficiency by reducing evapotranspiration and increasing light scattering, and contribute water and nitrogen inputs to soils. Currently, a major limitation in further assessing the effects of fog on vegetation, as well as changes in fog patterns under ongoing climate warming, is the scarcity of fog data with broad spatiotemporal coverage. To address this gap, we built three ensemble decision-tree machine learning models—Random Forest, LightGBM, and XGBoost—to predict fine-scale monthly fog frequency using ERA5-Land data and physiographic and temporal parameters. Hourly fog observations from 136 ASOS weather stations in California were used as ground truth, and spatial and temporal holdout strategies were applied to ensure generalization. Overall, the models effectively rank and classify monthly fog frequency across seasons, with the strongest performance during July and August, when dry spells are most prevalent in California. Our methodology demonstrates how large-scale climatic data can be paired with physiographic and temporal information to map fog frequency, with models that are agnostic to fog-formation mechanisms and transferable for use in other regions. Beyond frequency mapping, this work provides insights into the drivers of fog formation through Shapley Additive exPlanations (SHAP) analysis. Dewpoint depression was found to be the most influential predictor, making it a good candidate for informing projections of future shifts in fog patterns. While climate-change studies have focused on important climatic variables such as temperature and precipitation, little do we understand about how fog patterns have changed in the recent past, or will shift in the future. Our approach can serve as the basis for assessing both.
How to cite: Lolos, I. and Terry, T.: Mapping Fog Frequency: A Machine Learning Approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8182, https://doi.org/10.5194/egusphere-egu26-8182, 2026.
Accurately quantifying inorganic carbon dynamics in stream networks is essential for constraining estimates of catchment-scale carbon dioxide (CO₂) outgassing, identifying its sources (autochthonous vs. allochthonous), and assessing sensitivity to hydrological and geomorphological controls. However, most existing approaches rely on single-station measurements or simplified reach-scale models, neglecting transport processes, upstream–downstream connectivity, network topology, and spatial heterogeneity of lateral inputs. Here, we present a network-based sampling design coupled with a Bayesian modelling framework to estimate network-scale balances of dissolved inorganic carbon (DIC), alkalinity, pH, and dissolved oxygen (O₂).
We applied this framework to two headwater catchments with contrasting geology, climate, land cover, and hydrological regimes: Valfredda (5.3 km², north-eastern Italian Alps, Alpine climate) and Turbolo (6.9 km², southern Italy, Mediterranean climate). In both catchments, we conducted spatially distributed sampling of approximately 15 sites per network within a single day, measuring total alkalinity, dissolved CO₂, O₂, water temperature, pH, and discharge. Sampling was timed during periods of negligible gross primary production to minimize diel variability. This assumption was verified using continuous monitoring stations providing diel cycles of O₂, CO₂, and pH.
The framework models pixel-scale mass balances of DIC, O₂, and alkalinity by accounting for upstream and lateral inputs, in-stream production, atmospheric exchange, and downstream export. Instantaneous carbonate equilibrium is assumed to derive pH and CO₂ from alkalinity and DIC, allowing direct comparison with observations. Reaeration coefficients are estimated using empirical relationships based on hydraulic properties. The model enables the mapping of longitudinal biogeochemical patterns across entire stream networks and the derivation of network-scale carbon budgets.
The two catchments exhibit contrasting spatial dynamics. In the alpine Valfredda network, high headwater alkalinity associated with dolomitic lithology produces elevated initial DIC concentrations, while high turbulence promotes intense degassing, driving dissolved CO₂ concentrations toward atmospheric equilibrium downstream. In contrast, the Turbolo network is characterized by heterogeneous lithology and dense vegetation, generating diffuse, carbon-rich lateral inputs that sustain elevated CO₂ concentrations even in downstream reaches. In both systems, the model successfully reproduces observed spatial patterns, highlighting the importance of lateral inflows and network structure in shaping catchment-scale CO₂ dynamics.
At the network scale, carbon flux magnitudes and dominant pathways differ markedly between catchments. Despite similar wetted channel areas (~7000 m² in Turbolo and ~8300 m² in Valfredda), Valfredda releases more than four times more CO₂ per unit stream surface area (~1.45 vs. ~0.36 mol m⁻² d⁻¹), corresponding to total fluxes of ~12 000 and ~2500 mol d⁻¹, respectively. In Valfredda, CO₂ evasion is sustained almost equally by lateral inputs and in-stream respiration, whereas in Turbolo it is dominated by lateral fluxes. Higher gas exchange rates and lower alkalinity in Valfredda favor rapid atmospheric CO₂ release, while lower turbulence and higher alkalinity in Turbolo promote downstream DIC transport.
Overall, our results demonstrate that reliable estimates of riverine CO₂ emissions require explicit representation of spatial structure, hydrological connectivity, and coupled biogeochemical processes across stream networks, providing a generalizable approach for scaling carbon fluxes from point measurements to entire catchments.
How to cite: Presotto, F., Senatore, A., Durighetto, N., Perri, A. C., Botter, G., and Bertuzzo, E.: Inorganic carbon budget for two headwater stream networks with contrasting climatic and geomorphic controls, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3106, https://doi.org/10.5194/egusphere-egu26-3106, 2026.
Spatial heterogeneity in water and energy fluxes drives patterns of vegetation productivity and soil carbon and nutrient cycling across landscapes. However, most ecohydrological models either neglect lateral transfers or treat biogeochemical processes in a spatially decoupled manner, limiting their ability to reproduce observed catchment-scale patterns. We address this gap by extending the mechanistic ecohydrological model Tethys–Chloris–Biogeochemistry (T&C-BG) to a fully distributed configuration (T&C-BG-2D) that explicitly represents lateral routing of soil carbon and nutrients. The model is evaluated against long-term hydrological and biogeochemical observations from the Hafren catchment (UK) and the Erlenbach catchment (Swiss pre-Alps), where it successfully reproduces observed dynamics of several river solutes, including dissolved organic carbon, ammonia, and nitrate. To overcome the computational bottleneck of distributed model initialization, we further introduce a hybrid spin-up framework combining flux-tracking one-dimensional simulations with a random forest–based spatial extrapolation. This approach efficiently generates spatially heterogeneous and topography-informed initial conditions while reducing computational costs by up to 90%. Together, these advances enable efficient, spatially explicit ecohydrological–biogeochemical modeling across complex landscapes.
How to cite: Lian, T., Zhang, Z., Fatichi, S., Paschalis, A., and Bonetti, S.: Advancing distributed ecohydrological modeling of catchment-scale carbon and nutrient fluxes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5376, https://doi.org/10.5194/egusphere-egu26-5376, 2026.
Climate and land use changes can significantly impact ecosystem water quantity as well as quality. To understand the corresponding physical processes within a catchment, an ecohydrological-biogeochemical model that can simulate water, nutrients and vegetation dynamics simultaneously is therefore required. The recently developed spatially distributed model T&C‐BG‐2D has enabled the simulation of coupled vegetation, hydrological, and soil biogeochemical dynamics within catchments. However, its potential in exploring the impacts of different scenarios and interventions on ecosystems can be limited by computational costs due to grid representations. In this work, we present a semi-distributed abstraction framework for T&C-BG-2D to simulate hourly river discharge and chemistry (C, N, P, K, Ca, Si, Mg) at the (sub)catchment outlet with minimal computational costs. Leveraging recent available remote sensing and reanalysis datasets, an algorithm was developed to enable a novel calibration procedure for all key model parameters (e.g., soil properties, land cover, and vegetation traits) within the catchment across representative hydrological response units. The newly developed semi-distributed version T&C-BG-SD was benchmarked against the fully distributed T&C-BG-2D model in the Hafren (Wales, UK) and the Erlenbach (Swiss pre‐Alps) catchments. To further evaluate the suitability of the framework in representing different catchment characteristics, the performance of the model was then examined across multiple catchments in the US and UK spanning diverse climatic conditions and land covers.
How to cite: Paschalis, A., Zhang, Z., Lian, T., Gu, R., and Bonetti, S.: A semi-distributed ecohydrological modelling framework for catchment hydrology and river chemistry , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11543, https://doi.org/10.5194/egusphere-egu26-11543, 2026.
Permafrost thaw in northwestern Canada has accelerated in recent decades due to rapid warming and increased precipitation. The degradation of ice-rich permafrost transforms landscapes, triggering widespread mass-wasting features known as thaw slumps. Across the Peel Plateau in the Northwest Territories (Canada), these thaw slumps mobilize substantial volumes of materials rich in organic matter, nutrients, and other solutes. The lateral transport and deposition of thawed materials into streams shift hydrological, sedimentary, and geochemical regimes, with cascading effects on biogeochemical cycles, food webs, and water quality. Microorganisms play a pivotal role in mediating the processes that regulate ecosystem structure and function. Yet, the responses of microbial communities within slump-affected stream networks remain poorly understood.
To address this knowledge gap, we conducted a two-year (2022-2023) catchment-scale investigation in the 1,100 km2 Stony Creek watershed on the Peel Plateau. Our study tracked microbial community responses along the slump-stream continuum, including rill water runoff from seven thaw slumps, impacted headwaters, major tributaries, and a transect along the Stony Creek mainstem. We characterized microbial communities using 16S rRNA amplicon sequencing and combined these data with stream physicochemical properties, dissolved (DOC) and particulate organic carbon (POC) composition, and landscape metrics to identify drivers of microbial community response. We also assessed microbial functional potential and biomass production using marker gene-based functional predictions (PICRUSt2) and tritiated leucine incorporation experiments.
Connectivity between thaw slumps and streams produced pronounced shifts in microbial community composition. The extent of community divergence downstream of rill water inflow covaried strongly with the change in sediment loading and associated particulate organic matter. With stronger slump influence, microbial communities became progressively more associated with anoxic conditions and a reduced, low-energy carbon pool, reflecting a transition to a system dominated by POC. Further downstream, microbial community patterns in major tributaries and along the mainstem became increasingly mixed, suggesting that as larger areas of the catchment were integrated and in-stream processes became more complex in higher-order stream segments, the direct disturbance signal from thaw slumps became less dominant in shaping community structure. Despite this, biomass production was strongly correlated with DOC throughout the mainstem transect, even though DOC represented a small fraction of the total carbon pool relative to POC.
Through this work, we aim to document how microbial communities transform as thaw slump materials are transported through fluvial networks. Establishing these patterns is critical for understanding biogeochemical cycling in thermokarst-affected landscapes, where terrestrial-aquatic connectivity is pronounced. Collectively, our findings provide a baseline for microbial community dynamics in this region and complement comprehensive geochemical and carbon cycling data. As climate change and permafrost thaw intensify in Arctic ecosystems, understanding the role of microbial communities becomes increasingly important. By characterizing stream microbial diversity, predicting functional profiles, and microbial activity, we advance our understanding of the mechanisms driving biogeochemical changes and their broader impacts on food webs, water quality, and greenhouse gas exchange.
How to cite: Taskovic, M., Lanoil, B., and Tank, S.: Propagating effects of permafrost thaw slumps on microbial communities throughout Arctic stream networks, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8257, https://doi.org/10.5194/egusphere-egu26-8257, 2026.
Mediterranean catchments are strongly constrained by water availability, with pronounced seasonal contrasts that tightly couple hydrological processes and ecosystem functioning. Understanding how water fluxes regulate carbon uptake through Gross Primary Production (GPP) remains a key challenge in ecohydrology, particularly in Mediterranean regions where direct carbon flux measurements are scarce.
The aim of this study is to assess GPP at the catchment scale using a water-balance approach constrained by stable water isotopes (δ¹⁸O, δ²H). The method relies on the ecohydrological coupling between plant transpiration and carbon assimilation, quantified through water-use efficiency (WUE). Isotope-based partitioning of evapotranspiration is combined with WUE to derive basin-scale GPP.
The approach is applied to 11 Mediterranean catchments in Corsica (France), covering a wide range of spatial scales (15–950 km²), elevation gradients (sea level up to 2700 m), climatic conditions, and geological contexts (dominated by fractured granitic and metamorphic schists bedrock in the mountains and detrital sedimentary formations in downstream lowland areas). These catchments offer contrasted hydrological regimes, from perennial mountain rivers to strongly water-limited lowland coastal systems, making them a natural laboratory to investigate water–carbon interactions.
The methodology framework is based on one year of monitoring of rainfall and river water stable isotopes (δ¹⁸O and δ²H). Rainfall isotope data collected at 20 stations were used to generate isotope precipitation isoscapes, while river isotopes were monitored at 11 sites (one per catchment). These isotope datasets were combined with ERA5-Land climate data and CORINE Land Cover (CLC) vegetation information.
Monthly GPP calculated results reveal strong seasonal and spatial contrasts across the 11 Corsican catchments. GPP shows a pronounced Mediterranean pattern, with very low values during summer drought (often <20 gC.m⁻²) followed by a sharp recovery in autumn and peak values exceeding 200 gC.m⁻² during late autumn and early winter. The seasonal amplitude exceeds one order of magnitude, highlighting the dominant control of water availability on carbon uptake. Low-elevation and coastal catchments exhibit stronger summer GPP reductions than higher-altitude mountain and/or larger catchments, suggesting a buffering effect of elevation, groundwater storage capacity and geological context on ecohydrological functioning. However, some limitations remain regarding the difficulty to assess evaporation and thus transpiration values.
To better constrain the temporal dynamics of water fluxes underlying these patterns, an isotope-enabled hydrological model based on the J2000-iso framework is being developed. By improving the partitioning of hydrological fluxes, particularly evaporation and transpiration, this approach is expected to reduce uncertainties in GPP estimates and help to better link hydrological processes with ecosystem productivity.
Overall, this study provides one of the first basin-scale applications of isotope-based GPP estimation in Mediterranean environments at the regional scale and illustrates the potential of ecohydrological approaches to better quantify water–carbon coupling under ongoing climate change.
How to cite: Bouché, L., Garel, É., Guisiano, P.-A., Santoni, S., Watson, A., and Huneau, F.: Estimating Gross Primary Production in Mediterranean catchments using isotopic mass balance: A multi-source ecohydrological approach applied to Corsica (France), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5826, https://doi.org/10.5194/egusphere-egu26-5826, 2026.
Inter-basin water transfer is a crucial measure for improving ecological environments in arid regions, yet comprehensive quantitative assessments of its ecological water replenishment effects remain insufficient. Therefore, this study examines the inter-basin ecological water replenishment from the Yellow River Basin to the Shiyang River inland basin via the Jingtai Electric Irrigation Project. An evaluation system with eight indicators—water transfer volume, groundwater depth, groundwater storage change, ecological replenishment volume, water area, replenishment efficiency, population growth rate, and urbanization rate—was constructed from the "water resources-water ecology-society" perspective. The entropy weight method was used to determine indicator weights, and comprehensive effects from 2011 to 2024 were systematically assessed. Results show that over the 14-year period, cumulative water transfer reached 1.527 billion m³, groundwater depth recovered by 0.45 m, and the water area of Qingtu Lake, a terminal lake, expanded by 17.65 km² with an increase of 176.5%. The comprehensive evaluation index increased by 140.8%, rising from 0.30 in 2011 to 0.72 in 2024, demonstrating significant achievements in ecological restoration, groundwater recharge, and human settlement improvement. Although ecological water replenishment efficiency is constrained by conveyance losses and regional population continues to decline, systematic improvements in core indicators such as water transfer volume, groundwater, and water area have driven a leapfrog enhancement of comprehensive benefits. The research findings fully validate the comprehensive benefits and sustainability of inter-basin ecological water replenishment, providing scientific basis for safeguarding the ecological security of key lakes in arid basins.
How to cite: Yu, L., Jia, B., Wu, S., Wu, X., and Zhang, L.: Comprehensive Assessment of Ecological Water Replenishment Effects from Inter-basin Water Transfer in Arid Inland River Basins, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16238, https://doi.org/10.5194/egusphere-egu26-16238, 2026.
Disentangling the multi-scale processes that generate and maintain biodiversity is a central challenge in ecology, particularly within global biodiversity hotspots where conservation stakes are highest. Metacommunity theory provides a framework for this endeavor, but empirical tests in topographically complex landscapes remain scarce for microorganisms. Here, we investigate the hierarchical drivers of ostracod (Crustacea) metacommunity assembly in the mountains of southwestern China, a global biodiversity hotspot. We employed a multi-faceted analytical approach, combining community-level multivariate statistics (PERMANOVA, RDA/CCA) with species-level machine learning (ML). At the regional scale, PERMANOVA revealed highly significant differentiation in community composition among the Nu, Lancang, and Yuan river basins, confirming that watershed boundaries act as primary biogeographical filters. Within these basins, both constrained ordination and the ML ensemble consistently identified a powerful hydro-ionic gradient, defined by electrical conductivity, temperature, and altitude, as the dominant local environmental filter. Crucially, our analyses reveal that this natural gradient is significantly amplified by anthropogenic pressures; agricultural and urban land use systematically favors tolerant, generalist species by increasing turbidity and altering water chemistry, leading to the decline of sensitive specialists. Synthesizing these findings, we propose a hierarchical framework integrating regional hydrological connectivity with local environmental filtering. This research provides a clear empirical validation of metacommunity theory within complex river networks and offers a scientific foundation for a more robust, spatially explicit bioassessment strategy for freshwater ecosystem conservation.
How to cite: Wang, Q., Zhai, D., Fang, X., Jiang, P., Zhang, C., and Frenzel, P.: Watershed boundaries and human-amplified environmental gradients shape ostracod metacommunities in Yunnan, China, a biodiversity hotspot , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2607, https://doi.org/10.5194/egusphere-egu26-2607, 2026.
The effects of climate change on ecosystems were particularly pronounced in alpine regions. Most studies on alpine river ecosystems were conducted in the temperate and Arctic regions, primarily focusing on the effects of meltwater runoff variation, with limited attention on the subtropical regions, e.g., the Qinghai-Tibetan Plateau (QTP). Rivers on the QTP are experiencing significant environmental shifts due to both hydrological and hydrodynamic changes, which are altering the ecosystem characteristics of these highland rivers. However, understanding gaps still remain in the biodiversity, community composition and structure stability of these ecosystems, as well as their key ecological driving force. Using macroinvertebrates as indicator species, we characterized biodiversity, community structures and food web stability within river networks of the middle-lower Yarlung Tsangpo Basin, a typical alpine river basin along QTP’s margin. The mainstem (Yarlung) and two tributaries, i.e., Nyang River and Parlung Tsangpo River, exhibited increasing gradients of hydrodynamic intensity and meltwater runoff. We found that taxonomic structures of macroinvertebrates were different across spatial and temporal scales, with hydrodynamic intensity, rather than water temperature reported in the temperate and arctic regions, as the primary factor driving taxonomic composition. Biodiversity showed consistent unimodal response patterns to hydrodynamic intensity across scales. Specifically, γ diversity, representing the regional biodiversity, was highest in Nyang River, which was characterized by moderate hydrodynamic intensity among rivers. Within each river basin, α diversity also peaked at the moderate hydrodynamic intensity on the basin’s range. Regarding food web structure, we observed similar functional feeding groups’ composition but variable complexity and stability across rivers, and found that the effect of hydrodynamic intensity on the structure stability surpassed that of basal food sources. As hydrodynamic intensity increased, structural complexity also increased, while stability followed a unimodal response, with the food web being most stable at moderate hydrodynamic intensity. These findings highlight hydrodynamic conditions as the most critical ecological driver in subtropical alpine rivers. It is suggested that moderating hydrodynamic intensity may be an effective strategy to maintain high biodiversity, functional complexity, and food web stability, offering a promising approach for ecological optimization in high-altitude alpine rivers affected by ongoing climate change and anthropogenic activities.
How to cite: Luo, Y., Xu, M., and Zhou, X.: Modifying hydrodynamics offers a pathway to enhance ecosystem function of the Qinghai-Tibet Plateau rivers, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15559, https://doi.org/10.5194/egusphere-egu26-15559, 2026.
Turbidity and fine sediment are widely recognized as key stressors in river ecosystems; however, most ecological assessments rely on short-term concentration metrics that fail to capture the cumulative and time-lagged nature of turbidity impacts. This study proposes an integrated framework to quantify and predict biological responses to cumulative turbidity exposure using sensitivity-based indices and generalized additive models (GAMs).
Long-term suspended sediment (SS) exposure was quantified as cumulative dose (time-integrated SS concentration, mg·hour/L) over multiple antecedent periods (1, 3, and 6 months), including threshold-exceedance metrics describing the duration and magnitude of exceedance above ecologically relevant SS levels. Based on species-specific correlations with cumulative turbidity exposure, a novel Turbidity Sensitivity Index for benthic macroinvertebrates (TSI-BM) was developed by weighting taxa according to sensitivity classes derived from monotonic response patterns of Ephemeroptera, Plecoptera, and Trichoptera (EPT) assemblages. The index was applied to 22 monitoring sites in the upper North Han River Basin, Korea.
Results showed that TSI-BM exhibited a strong and consistent negative correlation with six-month cumulative turbidity exposure (Spearman’s ρ = −0.46, p < 0.001), outperforming conventional indices. GAM-based models further revealed nonlinear main effects and interactions among cumulative turbidity, hydraulic conditions (water depth and velocity), and nutrient concentrations on benthic community sensitivity, with site-wise cross-validated coefficients of determination (R²) ranging from 0.40 to 0.72.
Overall, this study demonstrates that cumulative turbidity exposure, combined with sensitivity-weighted biological indices and flexible nonlinear modeling, provides a robust approach for diagnosing and predicting ecological degradation under sediment stress. The proposed framework offers a transferable tool for river monitoring, impact assessment, and adaptive sediment management under increasing hydrologic variability.
This work was supported by the Korea Environmental Industry and Technology Institute (KEITI) through Aquatic Ecosystem Conservation Research Program, funded by Korea Ministry of Environment (MOE) (RS-2021-KE001374).
How to cite: Choi, M. and Ahn, J.: Quantifying Cumulative Turbidity Stress on Riverine Biota Using Sensitivity-Based Indices and Generalized Additive Models, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8836, https://doi.org/10.5194/egusphere-egu26-8836, 2026.
Forests serve as a major carbon storage in the Earth system, and accumulated biomass represents the net result of continuous carbon exchange through photosynthesis and respiration. Conventional yield-based inventory methods, operating at annual or multi-year temporal scales, are limited to capture underlying physiological processes. In this light, we develop a process-based model that simulates carbon uptake, respiratory losses, mortality, biomass growth, and evapotranspiration at daily temporal resolution. Photosynthetic and respiratory fluxes are dynamically regulated by temperature, solar radiation, vapor pressure deficit, and soil water availability, where the latter is computed from a rainfall–runoff model representing catchment-scale soil storage and water balance. Rather than prescribing evapotranspiration, the model allows it to adjust with vegetation growth, such that increasing biomass expands transpiration capacity under prevailing environmental conditions. In parallel, biomass accumulation reflects the portion of carbon retained by vegetation following atmosphere–biosphere carbon exchange, completing the coupled representation of carbon–water–vegetation interactions. Taking a forested catchment in South Korea as an example, a 100-year simulation reproduces expected patterns of forest development, from rapid carbon accumulation in early stages to reduced net carbon gain in mature forests due to physiological aging. Although generally consistent with inventory estimates, the model additionally reveals hydrologic and climatic controls in plant growth, particularly moisture limitation, which annual inventory approaches cannot diagnose. The framework enables physically grounded and continuous prediction of forest carbon accumulation, supporting more realistic carbon accounting, ecosystem monitoring, and climate policy evaluation.
How to cite: Lee, J. and Paik, K.: Integrating Hydrology and Plant Physiology in Forest Carbon Accumulation Modeling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-882, https://doi.org/10.5194/egusphere-egu26-882, 2026.
Posters on site: Fri, 8 May, 14:00–15:45 | Hall A
The accurate representation of vegetation and its dynamics plays a crucial role in the modelling of hydrological cycle. Vegetation regulates the movement of water and energy fluxes within an ecosystem. Process based models such as Soil and Water Assessment Tool Carbon (SWAT–C) are widely used to model different water balance components such as streamflow, evapotranspiration, soil moisture and sediment yield. However, their accuracy in simulating vegetation dynamics particularly, forest growth is limited for tropical and sub-tropical regions as the original model was developed for temperate regions. The unrealistic representation of forest phenology poses a limitation in estimating the Leaf area index (LAI), evapotranspiration and sediment accurately. This study adopted a climate triggered start of season for initiating the forest growth in a dry deciduous forest in sub-tropical region rather than a fixed calendar date for each year of simulation. Remote sensing data of Moderate Resolution Imaging Spectroradiometer (MODIS) LAI was utilised to derive the various growth parameters governing the shape of the ideal plant growth cycle. Different SWAT-C configurations were tested to evaluate the effects of parameterization and dormancy adjustments. While the default model simulated streamflow accurately, the forest dynamics was captured poorly leading to inaccurate LAI estimation, overestimation of evapotranspiration and sediment yield. Overall, the results revealed that the improved model would advance ecohydrological simulation accuracy by capturing vegetation-water interactions.
Keywords: Forest dynamics, Ecohydrology, LAI, Remote-sensing.
How to cite: Agarwal, A. and Vema, V. K.: Integrating Satellite-Derived Parameters to Advance Ecohydrological Modeling of Forested Areas, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-588, https://doi.org/10.5194/egusphere-egu26-588, 2026.
To formulate resilient water management strategies, policymakers require tools that can simultaneously simulate hydrological variability and dynamic sectoral demands. This research introduces a coupled modeling framework that links the Soil and Water Assessment Tool (SWAT) with the Water Evaluation and Planning (WEAP) model to quantify future water stress. We applied this integrated approach to the Chaliyar River Basin (CRB), driving the models with bias-corrected climate projections from 13 CMIP6 General Circulation Models. Hydrological simulations indicate a marked rise in peak flows driven by intensifying extreme rainfall events, although low flow conditions remain relatively stable. On the demand side, agriculture remains the primary consumer, driving total annual water requirements from a baseline of 1,143.2 MCM (2015) to projected levels of 1,289 MCM under SSP2-4.5 and 1,245 MCM under SSP3-7.0 by the century's end. Notably, the assessment identifies counter-intuitive vulnerability patterns: the intermediate SSP2-4.5 scenario results in higher overall unmet demand compared to the high-emission SSP3-7.0 scenario. Specifically, the agricultural sector faces critical shortages, with unmet demand reaching 26.5% under SSP2-4.5 versus only 5.3% under SSP3-7.0. These results validate the proposed coupled framework as a transferable solution for assessing sectoral water security in climatologically comparable river basins.
How to cite: Sudheer, K. P., Nizar, S., Senan, S., Sivan, S., Thomas, J., Vema, V. K., and Jainet, P. J.: Quantifying Sectoral Water Stress under future Projections: Insights from a Coupled SWAT-WEAP Analysis, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6939, https://doi.org/10.5194/egusphere-egu26-6939, 2026.
Urban flooding is a significant challenge in most cities worldwide, largely due to intensified rainfall extremes and unplanned urban development. Dense settlements have resulted in limited scope for augmenting or retrofitting existing stormwater management structures. Low Impact Development (LID) can restore the hydrology of urban areas by using decentralised stormwater control and transforming it into its natural state. It's critical to understand the extent to which a city can employ a LID, often known as its flood adaptive capacity.
While several studies have attempted to quantify urban adaptive capacity for LID implementation, much of this work focuses on broad vulnerability or resilience indicators rather than the realistic placement of LIDs. This creates a gap between high-level assessments and the practical realities of placing LID measures in specific urban contexts. In practice, LID effectiveness is highly condition-dependent and requires high-resolution spatial information like land use, available space, slope, and surface characteristics. However, most cities lack the high-resolution spatial information and systematic assessment frameworks needed to determine where different LID measures can be realistically implemented. To address this limitation, we have developed a framework that derives those data and assesses the adaptive capacity of a city for implementing LIDs.
As part of this approach, the framework requires high-resolution urban land use/land cover (LULC) data, which we have generated through a multi-stage mapping framework that integrates SegFormer (Vision Transformer) based semantic segmentation with OpenStreetMap (OSM) geometric refinement. The model combines the Sentinel-1 SAR backscatter with Sentinel-2 optical composites to create a multi feature stack which is then used by SegFormer-B0/B1 model. From this refined LULC, key hydrologic indicators were derived, including percent imperviousness, runoff coefficients and available rooftop/pervious area for LIDs.
Further to derive the adaptive capacity an Analytical Hierarchy Process (AHP) in combination with entropy and fuzzy method of based weighted overlay is applied to compute suitability maps for major LIDs using historical flood extent, slope, impervious surface ratio, soil infiltration characteristics (HSG), groundwater depth, derived LULC map, road width and traffic intensity. These suitability maps were converted into an adaptability metric by estimating the fraction of locations that remain feasible for implementation after applying LID-specific constraints.
The result highlights that in highly urbanized cities like Delhi where there’re is no place for Nature Based LIDs, implementing decentralized Rain barrels with only 37mm capacity per household can reduce the flood by 75%. Overall, the proposed framework provides a pathway from LULC mapping to city scale LID adaptability assessment and enables evidence-based decision making for sustainable decentralised stormwater management.
How to cite: Aryal, A. and An, R.: An Integrated Framework for Assessing the Adaptive Capacity of Cities to Implement LIDs Using LULC Mapping, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6283, https://doi.org/10.5194/egusphere-egu26-6283, 2026.
Physics-based lake hydrodynamic models require high-resolution forcing data to simulate thermal structures accurately. However, many lakes lack complete inflow/outflow measurements. In natural lakes, outlet hydrodynamics can correct outflows to artificially close the water balance, but this option is generally not available in managed reservoirs. This forces modelers to rely on backward water balance calculations based on changes in observed lake storage to determine a fixed time series for missing flows. This approach often fails during model calibration. Indeed, evaporation in these models is calculated using model parameters that may be adjusted during the calibration, leading to cumulative errors in the simulated storage or the need for frequent, time-consuming model warm restarts. In addition, unmeasured flows needed for balance closure are often attributable to various processes, which leads to ambiguity regarding where in the lake they happen, and about the water quality (e.g., temperature and nutrients) in these flows. Both affect vertical processes.
To address this, we develop a Machine Learning emulator that maps hydrodynamic model parameters directly to the unmeasured flow required for water balance closure. Using the General Lake Model (GLM), a state-of-the-art vertical 1D hydrodynamic model, and a water supply reservoir in England as a case study, we follow a four-stage methodology: (1) Sensitivity Analysis for dimensionality reduction using the Method of Morris; (2) an optimization routine to define target unmeasured flows over a 10-year period; (3) emulator training using Random Forest Regression (RFR) and (4) validation on the reservoir storage.
The RFR emulator achieves very high predictive accuracy (R2 = 0.99) while estimating the optimised unmeasured flows. In addition, it identifies water treatment losses – which recirculate to the reservoir – as the primary unmeasured flow. This finding corroborates operator evidence and accounts for a crucial uncertainty in the calibration. While long-term stability remains sensitive to secondary parameters and the training data size, the emulator using RFR significantly reduces cumulative storage errors compared to the traditional approach that uses fixed unmeasured flows, minimising the need for frequent model restarts and substantially decreasing total calibration time.
How to cite: Onen, M. O., Rougé, C., Douterelo Soler, I., and Darch, G.: Automating Water Balance Closure in Lake Hydrodynamic Models: a Machine Learning Approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7992, https://doi.org/10.5194/egusphere-egu26-7992, 2026.
Vapor pressure deficit (VPD) is projected to strongly increase over land areas under future global warming due to rising air temperature and declining relative humidity. Understanding the impacts of VPD on the water cycle, particularly evapotranspiration (ET), is therefore critical for delineating better water management strategies. It is commonly assumed that higher VPD enhances the atmospheric demand for water and increases ET – especially in non-water-limited regions. However, this assumption disregards plant physiological and biophysical controls that can override atmospheric demand for water. Elevated VPD can lead to stomatal closure and a decrease in transpiration and thus ET. Moreover, higher VPD always co-occurs with warmer temperatures, which may exacerbate plant water stress or inhibit enzyme activity, further suppressing plant growth and reducing ET. When plant controls dominate over atmospheric demands, ET may decrease with increasing VPD at the annual scale. Here, we tested this hypothesis across mainland Southeast Asia using a mechanistic model (T&C) and remote sensing products. After a model testing with available flux tower data, we run T&C at very high resolution (1km2) over a domain of 2.93 million of km2 for a period of 13 years (1998-2010). We found that around 30% of mainland Southeast Asia exhibits decreasing ET with higher VPD. Specifically, when the background VPD (mean annual) exceeds ~1150 Pa, ET starts decreasing and decreases faster with higher VPD. Under future global warming and rising VPD, such ET reductions may lead to diminished land-atmosphere moisture exchange, potentially amplifying local atmospheric dryness. These findings provide a new perspective on the nonlinear responses of ET to VPD and improve our understanding of hydrological response under future climate change over a large and understudied area such as Southeast Asia.
How to cite: Ren, J., Luo, Z., Luo, X., Ivanov, V. Y., Paschalis, A., Galelli, S., Mahto, S. S., Vu, D. T., and Fatichi, S.: Opposing evapotranspiration responses to rising vapor pressure deficit in mainland Southeast Asia, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8672, https://doi.org/10.5194/egusphere-egu26-8672, 2026.
Freshwater systems play a disproportionately important role in global carbon cycling, yet the contribution of algal primary productivity to the production and transformation of dissolved organic matter (DOM) remains poorly researched, particularly with respect to fluorescent dissolved organic matter (FDOM). While protein-like fluorescence is widely associated with autochthonous microbial activity, humic-like fluorescence has traditionally been attributed to terrestrial inputs, despite emerging evidence for its in-situ microbial production. This study investigates the role of freshwater algae in the production, composition and temporal dynamics of protein-like and humic-like FDOM under controlled laboratory conditions. A previously developed simulated freshwater (SFW) model, free from external dissolved organic carbon inputs was optimised for algal growth and monitored for algal-derived fluorescence signatures using bench top fluorescence spectroscopy. Monoculture and mixed algal communities were grown under defined nutrient regimes, spanning low to elevated concentrations representative of nutrient enrichment and bloom conditions. We quantify algal primary productivity using single-turnover active fluorometry (STAF), providing high-resolution insight into photosystem II efficiency and productivity dynamics. Excitation–emission matrix spectroscopy is applied throughout algal growth phases to characterise changes in FDOM intensity, composition and persistence, with particular focus on protein-like and humic-like components.
Findings show a coupling of primary productivity measurements with algae derived fluorescence signatures. This research aims to investigate the dynamics between algal metabolism, nutrient availability and FDOM production. The findings will improve understanding of algal contributions to the cycling of DOM in freshwater systems and identify the role and usefulness of fluorescence-based monitoring tools, particularly in environments experiencing nutrient enrichment and increasing algal biomass.
How to cite: Coombs, M., Tulloch, C., Perrett, R., Thorn, R. M. S., Attridge, J. W. A., and Reynolds, D. M.: Investigating Algal Primary Productivity and In Situ Production of Aquatic Fluorescent Organic Matter in a Simulated Freshwater System , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14465, https://doi.org/10.5194/egusphere-egu26-14465, 2026.
Algae play a core role in sustaining river ecosystem health as primary producers, but excessive nutrient inputs can trigger uncontrolled growth and algal blooms, posing serious ecological risks. Hence, identifying vulnerable river segments is of importance to assess eutrophication risk and prioritize management actions, which in turn requires representing algal spatial distribution across entire river networks rather than isolated reaches. Nonetheless, achieving such network-scale characterization is particularly challenging in regulated river systems, where hydraulic structures modify flow regimes, disrupt longitudinal connectivity, and alter nutrient transport, thereby reshaping spatial patterns of algal communities. To address this challenge, we develop a parsimonious mechanistic model that explicitly reflects dam-induced hydrological alterations while retaining a minimal set of state variables and parameters. The model builds upon the Coupled Complex Algal–Nutrient Dynamics (CnANDY) model, a parsimonious process-based model that simulates interactions between pelagic and benthic algae competing for a single limiting nutrient and light along river networks. We extend the original CnANDY model by incorporating additional modules describing the physical effects of dams and associated reservoir characteristics, resulting in the CnANDY-dam model, which enables prediction of algal dynamics under hydraulic regulation at the river-network scale. As a baseline validation step, the original model is first applied to the Gyeongan River watershed (~506 km²), an unregulated sub-basin of the Han River, the largest river basin in South Korea, to evaluate model behavior under flow conditions unaffected by upstream regulation. River network structure, including Horton–Strahler stream order and hydraulic geometry, is derived from geomorphic observations. To approximate steady-state conditions, monthly mean runoff (March-November) and phosphorus (P) inputs are estimated using observations from 2017-2022, with non-point source P loads derived from land-use data and point source P loads obtained from wastewater treatment plant records. The original model reproduces stream-order-dependent patterns of algal dominance, with benthic algae prevailing in low-order streams and pelagic algae dominating in higher-order reaches, driven by differences in hydraulic geometry features and nutrient uptake. Building on this validated model, the extended CnANDY-dam model is applied to a regulated sub-basin of the Han River to demonstrate its workability under hydraulic regulation. The application of the CnANDY-dam model is expected to confirm its capacity to represent algal–nutrient dynamics under hydraulic regulation at the river-network scale.
Acknowledgements
This work was supported by the Creative-Pioneering Researchers Program through Seoul National University and by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. RS-2025-00523350).
How to cite: Joo, H. and Yang, S.: Parsimonious Mechanistic Modelling of Dam Effects on Coupled River Algae-Nutrient Dynamics, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6413, https://doi.org/10.5194/egusphere-egu26-6413, 2026.
Wild Streams in Taiwan are characterized by steep channel slopes, rapid flow velocities, short channel lengths, and small watershed areas. These streams are highly susceptible to severe compound flood and sediment disasters triggered by typhoons and intense rainfall. To safeguard human life and property in surrounding areas, river management has historically emphasized engineering safety and disaster mitigation. Consequently, ground sills were widely installed to stabilize riverbeds and reduce channel erosion, while the potential ecological impacts of such engineering measures were largely overlooked, often resulting in severe degradation of river ecosystems. With the extensive installation of ground sills, river environments have become increasingly homogenized. The height configuration of the structures can alter hydraulic conditions and longitudinal connectivity, as well as modify the natural diversity of flow types (e.g., shallow flow, riffles, runs, and deep pools), leading to a decline in biodiversity. As a result, aquatic ecosystems and fish habitats have been significantly disturbed, causing degradation of river ecological functions. This has prompted efforts to restore and rehabilitate rivers whose ecological functions have been degraded by human interventions.
The object of investigation in this study was the Tengqiao Creek and the Two-Dimensional Habitat Diversity Construction Model was applied to simulate and investigate changes in fish habitat types and the spatial distribution under different discharges and varying heights of ground sills. Habitat diversity was quantified using the Shannon index as the Habitat Diversity Index (HDI). The results indicate that, under all discharge conditions and ground sill heights, habitat types 1(shallow pool) and 2 (medium pool) account for the largest proportion of habitat area within the study reach. When discharge is lower than 0.04 cms and the ground sill height is below 0.5 m, habitat type 3 (deep pool) does not occur; the area of habitat type 3 increases with increasing structure height. The area proportions of habitat types 4 (slow riffle), 5 (fast riffle), and 6 (run) are considerably smaller than those of types 1 and 2, with type 4 occupying a relatively larger area than types 5 and 6. When the ground sill height exceeds 0.75 m, the areas of habitat types 4, 5, and 6 are significantly smaller than those observed under structure heights below 0.75 m. Across all flow conditions, the habitat diversity index increases with increasing discharge but exhibits a decreasing trend as the height of ground sills increases. The findings of this study provide valuable references for future river restoration and ground sill design.
How to cite: Chen, C.-N., Chen, K.-T., Huang, C.-T., Kuo, C.-M., and Tsai, C.-H.: Assessing the Effects of Ground Sill Height on Fish Habitat Diversity: A Case Study of Tengqiao Creek, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6415, https://doi.org/10.5194/egusphere-egu26-6415, 2026.
Contemporary freshwater resource management seeks to simultaneously secure sufficient quantity and adequate quality for domestic, agricultural, livestock, and industrial uses, as well as to mitigate water-related risks. While river discharge and water level magnitudes have been extensively gauged worldwide, monitoring river water quality remains sparse in both spatial coverage and temporal resolution, largely due to substantial manpower and financial investment required. These limitations are further compounded by the frequent misalignment between hydrological watershed boundaries and administrative units, which complicates the direct integration of water quality measurements with corresponding river discharge records. Consequently, previous studies have typically been confined to a limited number of subbasins when investigating temporal trends and concentration-discharge (C-Q) relationships. Overcoming these limitations requires a coupled temporal perspective, in which the co-evolution of discharge and water quality can be systematically examined to understand watershed responses to changing climate conditions and to track the effectiveness of water management actions. In this study, we leverage 11 years (2014–2024) of hourly and daily observations from an automated national water quality monitoring network in South Korea, encompassing temperature, pH, total nitrogen, total phosphorus, and total organic carbon. This unique dataset enables coupled temporal analyses of river water quantity and quality trends across river networks spanning the country’s four major basins. Mann-Kendall test shows increasing trends in discharge at most gauging stations, contrasting with the largely insignificant trends reported during the 20th century. However, four homogeneity tests (Pettitt, Buishand, von Neumann, and standard normal homogeneity test) indicate that these increases are attributable to distinct change points rather than gradual monotonic trends. Although homogeneity tests are traditionally applied to identify artificial discontinuities caused by station relocations or changes in data-quality control procedures, the found change points here appear to reflect hydrological responses to climatic forcing. By jointly applying trend and homogeneity analyses to both discharge and water quality variables, we examine how abrupt hydrological shifts propagate through physiochemical, nutrient and organic carbon dynamics at the national scale. Understanding whether water quality responses to discharge regime changes are concurrent, lagged, or threshold-driven provides pivotal insight for total maximum daily load management and for assessing eutrophication risk under a changing climate.
Acknowledgements
This work was supported by the Creative-Pioneering Researchers Program through Seoul National University and by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. RS-2025-00523350).
How to cite: Kang, H. and Yang, S.: Coupled temporal trends in river discharge and water quality across South Korea, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6425, https://doi.org/10.5194/egusphere-egu26-6425, 2026.
With climate change, extreme rainfall events are expected to occur more frequently, leading to more landslides triggered by climate incidents. Landslide processes in a dynamic environment in Taiwan play a crucial role in driving physical erosion and chemical weathering, facilitating the water-rock interaction and the transport of terrestrial dissolved and particulate materials through river systems, thereby affecting elemental chemistry and carbon cycling. This relationship between physical erosion and the resultant weathering affects the sequestering of carbon dioxide through silicate weathering and further links between erosion in the landslide-active catchment area and climate change. However, our knowledge of the effects of landslide weathering on river water chemistry, weathering processes, and the relationship with carbon cycling remains limited, and the absence of reliable chemical indicators to evaluate these processes necessitates further study. Here, we address the effects of landslide-related weathering on water chemistry (elements and isotopes) and carbon cycling in Taiwan. Major and trace elements, related isotopes, and carbon concentration were analyzed in the water samples from the river water beside landslides and leakage from landslide deposits. This study aims to characterize variations in river chemistry associated with landslide-affected settings and explore potential chemical and isotopic indicators to evaluate landslide-related weathering processes. The preliminary results show that the waters influenced by landslides can show distinct chemical characteristics relative to nearby river water. Silicate weathering dominates the dissolved load (>80%), while sulfate appears to co-vary with the total dissolved solids, suggesting an additional sulfate-linked control on hydrochemical variability. Dissolved uranium isotopes reflect the degree of physical erosion, and show a negative correlation with the silicate chemical weathering, which reflects a weathering limited condition in our study area. This study will help refine chemical indicators for assessing landslide weathering signals and improve understanding of the mechanism of landslide-weathering-river chemistry linkages, as well as the carbon export in mountainous rivers under a changing climate.
How to cite: Wang, R.-M. and Huang, K.-F.: Variations in river chemistry in Taiwan’s mountainous rivers: Influences of landslides and weathering, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15424, https://doi.org/10.5194/egusphere-egu26-15424, 2026.
Water from precipitation and constituents from multiple sources are integrated along river networks and exported at catchment outlets after undergoing hydrological and biogeochemical processes. Accordingly, stream water quantity and quality exhibit emergent behaviors rather than reflecting a simple sum of inputs, typically expressed as power-law relationships between discharge (Q) and concentration (C) which distinguish water quality parameter’s export behavior (C–Q pattern), and as temporal persistence (memory) in riverine output. How catchments generate these characteristics has long been of interest. Previous studies have shown that source availability governs which C–Q pattern emerges, and that catchment filtering of stochastic inputs can generate legacy sources that produce memory. These findings naturally raise core follow-up questions: (1) Even when the same C–Q pattern emerges, what controls variations in its intensity?; (2) Does catchment filtering invariably lead to the formation of legacy sources?; and (3) given that both C–Q patterns and memory arise from catchment filtering, do they share common underlying physical drivers? To address these questions, we aim to examine how catchment characteristics affect C–Q patterns and temporal memory formation, and whether systematic linkages exist between them. Across 24 catchments in South Korea, we analyze daily precipitation and discharge data along with 8 water quality parameters (pH, EC, DO, TOC, TN, TP, Turbidity, and Chlorophyll-a). To investigate catchment spatial characteristics that account for source availability and existence of legacy sources, we employ 14 explanatory variables representing catchment geography, land use, social indicators, and water-use characteristics. The C–Q pattern analyses report that, for some nutrients, the pattern in which concentrations increase with discharge due to unlimited non-point sources is consistent across all catchments, but the increasing magnitude gets sharper in natural catchments. This indicates that the relative contributions of point and non-point sources act as a key factor that shapes C–Q patterns. Temporal memory is examined using power spectrum analysis. Our results show that under natural cover conditions - where legacy sources are more likely to form – river discharge tends to exhibit long-term memory; however, for some ionic parameters, short-term memory gets strengthened. This suggests that persistent input signals from anthropogenic sources are disrupted during the catchment filtering process. Finally, for discharge-flushed water quality parameters, we identify a decreasing power-law relationship between C–Q patterns and memory, suggesting that surface-runoff-dominated export of water quality parameters represents a stochastic input signal that is not buffered through soils, and therefore its intrinsically memoryless signal is preserved. These findings corroborate a process-based understanding of catchment filtering mechanisms and provide a scientific basis for integrated monitoring and management of water quantity and water quality at the catchment scale.
Acknowledgements
This work was supported by the Creative-Pioneering Researchers Program through Seoul National University and by the National Research Foundation of Korea (NRF) grant funded by the Korean government (Ministry of Science and ICT) (No. RS-2025-00523350).
How to cite: Lee, E. and Yang, S.: Deciphering catchment filtering effects on export regimes and temporal memory of river water quantity and quality, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6429, https://doi.org/10.5194/egusphere-egu26-6429, 2026.
Photosynthesis, quantified as gross primary productivity (GPP), and evapotranspiration (ET) are two fundamental processes in coupled water and carbon cycles. The strong regulation of ecosystem on carbon and water fluxes by stomata is well understood at the leaf level. However, the coupling is complex at regional or ecosystem scales. The objective of this study is to understand key environmental factors that control both water and carbon fluxes at regional scales and develop a robust resource-constrained framework (RCF) for estimating climatology of coupled ecosystem carbon and water fluxes. Water balance data from 1927 catchments were obtained to parameterize the model and independent observations from 107 flux stations were used to validate the method. Results demonstrated robust model performance with Nash–Sutcliffe efficiency (NSE) of 0.65 for GPP and NSE of 0.55 for ET against independent flux observations. The RCF approach estimated global mean GPP and ET at 1141 g C m⁻² a⁻¹ and 530 mm a⁻¹, respectively, corresponding to an annual terrestrial carbon uptake of 142.4 Pg C a⁻¹. Further analysis identified the ecosystem energy and water limited regimes, with about 40% land areas energy-limited, 40% water limited, and 20% co-limited for both GPP and ET across globe. This study reveals consist estimates of GPP and ET by disentangling the spatial interplay of energy and water constraints. The RCF approach provides a transparent and scalable approach to jointly estimate and attribute carbon and water fluxes, offering new insights into ecosystem functioning and a pathway to improve coupled ecosystem modeling.
How to cite: Wang, S., Zhang, L., Wang, Y., Cheng, L., Zou, K., Lei, X., Liu, W., Wang, Y., and Liu, P.: A generalized resource-constrained framework for quantifying coupled ecosystem water and carbon fluxes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5007, https://doi.org/10.5194/egusphere-egu26-5007, 2026.
Posters virtual: Tue, 5 May, 14:00–18:00 | vPoster spot A
EGU26-9012 | ECS | Posters virtual | VPS8
Ecohydrological Modelling of Annual Water Yield and Water-Related Ecosystem Services in the Semi-Arid Region of Warangal, IndiaTue, 05 May, 14:39–14:42 (CEST) vPoster spot A
Urban and peri-urban regions in semi-arid India are increasingly exposed to contrasting climatic extremes, namely water scarcity and flooding, driven by complex interactions between anthropogenic pressures and biophysical processes. In this context, the present study investigates long-term changes in the annual water yield (AWY) ecosystem service across sub-watersheds of the Godavari River Basin encompassing the semi-arid Warangal district, Telangana, India. The InVEST AWY model is applied for two representative years, 1995 and 2025. The results indicate that AWY ranges from 460-890 mm yr⁻¹ in 1995, with relatively higher values in the north-eastern sub-watersheds, but declines across most sub-watersheds by 2025 to 220-690 mm yr⁻¹. The annual precipitation found to be 1400 to 1230 mm yr⁻¹ over the study period, while potential evapotranspiration increase substantially from 2253 to 2955 mm yr⁻¹, enhancing atmospheric evaporative demand and reducing water availability. Sensitivity analysis (expressed in terms of elasticity, E), shows that AWY is highly sensitive to precipitation variability (E = 1.84) and moderately negatively sensitive to urban-related biophysical parameters (root restricting depth: E = -0.42, crop coefficient (Kc): E = -0.39). In contrast, sensitivity to potential evapotranspiration is lower (E = -0.36), highlighting the combined influence of climatic forcing and urban expansion. Spatially, urban land use in 1995 is concentrated in the central region, with cropland and forest dominating the western and eastern parts, respectively, yielding a mean AWY of 718.51 mm yr⁻¹. By 2025, relatively higher AWY zones shift toward the north-eastern region, reflecting reduced evapotranspiration associated with urban expansion; however, the overall mean AWY declines to 476.36 mm yr⁻¹, indicating that land-use changes influenced spatial patterns while climatic factors governed the temporal decline. The decline in AWY between 1995 and 2025 corresponds with reduced ecosystem service values (ESV) for water-yield related regulation services, particularly water regulation (ESV1995 = 16.37 to ESV2025 = 12.91 million US$) and water supply (ESV1995 = 84.73 to ESV2025 = 73.69 million US$). Overall, the findings demonstrate the joint role of climate variability and urbanization in shaping sub-watershed water yield and associated ecosystem services, providing insights for climate-responsive urban and landscape management.
How to cite: Dasari, S., Pal, M., and Keesara, V. R.: Ecohydrological Modelling of Annual Water Yield and Water-Related Ecosystem Services in the Semi-Arid Region of Warangal, India, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9012, https://doi.org/10.5194/egusphere-egu26-9012, 2026.
