We invite contributions on field and laboratory measurement techniques, as well as the development, validation, and application of numerical models to simulate multiphase flows and morphological processes across spatiotemporal scales. Topics of interest include (but are not limited to):
• Innovative measurement techniques for suspended and bed load transport using optical, acoustic, and traditional methods.
• Sediment characterization and calibration of critical bed shear stress for cohesive and non-cohesive sediments.
• Numerical modeling of sediment transport, including flocculation, bed armoring, and morphological evolution.
• Integration of measurement networks and multi-point datasets for model validation.
• Simulation of sediment management strategies for hydropower, navigation, and flood protection.
• Design and evaluation of restoration measures for rivers and aquatic environments.
• Eco-hydraulics, focusing on flow, sediment, and vegetation interactions.
Advances in computational power and AI-driven techniques now enable high-resolution simulations of sedimentary and hydrodynamic interactions, supported by high-quality validation data. These innovations provide new insights into dune development, riverbed armoring, and long-term morphological changes affecting flood security and ecosystem health.
This session encourages submissions that integrate measurement and modeling, highlight AI applications, or present case studies across diverse water environments. By fostering interdisciplinary collaboration, it aims to advance understanding of sedimentary and hydro-morphological dynamics in shaping aquatic systems
Orals: Thu, 7 May, 14:00–18:00 | Room 3.16/17
The physical and mechanical characteristics of gas-free aquatic muds govern methane bubble descriptors such as size, shape, and orientation. Here, we quantify these mud characteristics in Lake Kinneret (Israel) using four gravity cores (A, B, C, and D: 1.5 to 2.45 m length, taken along few hundred meters at NW transect from 27.5 to 38 m water depth). Depth-dependent undrained shear strength was measured using a pocket shear vane and was also estimated numerically, both showing an increasing trend with depth, with maximum values of 1.8 kPa (A at 1.55 m), 1.6 kPa (B at 1.75 m), 4.7 kPa (C at 2.33 m), and 2.7 kPa (D at 2.15 m). The suspension–sediment interface corresponded to density transitions at ρ = 1.28 g/cm³ at 0.675 m (A), ρ = 1.27 g/cm³ at 0.775 m (B), ρ = 1.20 g/cm³ at 0.625 m (C), and ρ = 1.11 g/cm³ at 0.525 m (D). Basic geotechnical index properties indicate water-rich, highly porous muds: water contents decrease with depth (including within suspension zone) from 329% to 122% (A), 311–109% (B), 372–112% (C), and 461–116% (D); porosity falls from ~90 near the top of the cores to ~76% at 1.75 m (A) and 1.55 m (B), and from >85–90% at the tops of cores C and D to ~70–75% at their bases. Atterberg limits are nearly constant, with LL ≈ 67% and PL ≈ 37% in cores A and B, and LL ≈ 75%, PL ≈ 32%, and an average PI ≈ 43 in cores C and D, consistent with high-plasticity silty clays. Dynamic Young’s modulus, evaluated from ultrasonic P-wave velocities, yielded irregular profiles in intact cores (ranging between ~500 m/s and ~1490m/s), which we attribute to presence of cracks and voids (from which methane gas escaped at the core retrieval), whereas remolded muds where the voids were eliminated, exhibited a monotonic increase in sound speed with depth, in the range from 1462m/s to 1492m/s. Further, Young’s modulus, small-strain shear modulus, and Mode I fracture toughness were derived from the Atterberg limits, while fracture toughness was inferred from empirical correlations with shear strength. Overall, our results demonstrate that Atterberg limits and basic geotechnical indices provide an effective framework for predicting small-strain stiffness and fracture properties of the aquatic muds, offering essential input for improved quantification of methane bubble descriptors in acoustic models.
How to cite: Geng, X., Katsman, R., Zhutovsky, S., Be'eri-Shlevin, Y., Uzhansky, E., and Katsnelson, B.: Evaluation of Mechanical and Physical Characteristics of Aquatic Muds by Geotechnical Methods, for Assessment of Methane Bubble Descriptor, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1593, https://doi.org/10.5194/egusphere-egu26-1593, 2026.
The transportation of bed load is an integral component of the morphology and functionality of river systems. This phenomenon is of paramount importance for the morphological appearance and availability of habitats. However, the process of recording this phenomenon has proven to be challenging. This article synthesizes two decades of Austrian experience with slot samplers for direct bedload measurement in alpine rivers and steep streams, providing a consolidated design overview and practical guidance for future installations and showing already known limits and challenges of this direct measuring method. A comprehensive description is provided of all configurations that have been deployed over the years, ranging from early shaft slot samplers to hydraulically liftable systems with optimized sealing and flushing mechanisms. Preliminary field observations indicate that, despite the availability of ample storage capacity, extreme events can impede measurement duration due to rapid filling. Maintaining watertightness and preventing sediment ingress in narrow, morphodynamically active channels continue to be pivotal challenges. Methodologically, slot samplers facilitate uninterrupted mass increase during flood events and grain-size characterization. However, their applicability is constrained by capacity, maintenance demands, and an upper grain-size limit. This limitation can be mitigated through appropriate design and complementary surrogates. Recent generations have enhanced deployment options during flood events through remote opening mechanisms and improved sample representativeness through the implementation of lifting mechanisms, lids with circumferential surfaces ("shoebox" lids), and flushing techniques. The integrated monitoring stations under consideration in this study couple direct slot samplers with geophone- and acoustic-based surrogates. These monitoring stations are site-calibrated to resolve event dynamics, hysteresis, and seasonal trends. In Austria, three torrents and two alpine gravel-bed rivers have been equipped with these systems; the first system was installed in 2006, and the latest liftable slot sampler (2.0) was completed in 2025. The following key findings from monitoring were identified: i) Event-long, complete grain-size distributions; ii) Continuous quantification of transport via weighing; iii) Detection and monitoring of selective transport; and iv) Successful sampling and calibration during floods with return periods up to 30 years.
How to cite: Rindler, R., Unger, L., Schwarz, S., Shire-Peterlechner, D., Lammer, A., and Habersack, H.: Austrian Slot Samplers in Alpine Streams and Gravel Bed-Rivers: Methodological Synthesis, Technical Development, and Operational Limits, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19319, https://doi.org/10.5194/egusphere-egu26-19319, 2026.
The bedload threshold of two fine sands S1 and S2 (D50 = 328 and 210 µm) were investigated in two different flumes: a recirculating flume (CH1) and an overflow flume (CH2) (Figure 1). Table 1 summarizes the characteristics of both flumes. In CH1, the sandy layer has a thickness of δ = 0.02 m and is placed on the fixed bottom. In CH2, the sediments were deposited in a pit extending over a 1.0 m length with a thickness of δ = 0.05 m. The bed thickness and the slopes (1:3) are consistent with the study of Van Rijn et al, (2019). For both flumes, the sediment bed is located in a fully developed flow area, and the water depth was maintained at d = 0.15 m. The main objective of this study was to configure CH2 to enable to study the threshold of motion of sediment particles using the image correlation method developed at the LOMC laboratory by Vah et al. (2020). This non-intrusive technique provides a highly sensitive and objective measurement compared to traditional techniques.
The image correlation method identifies the bedload threshold (Ubl) by analyzing the decorrelation between a reference initial image of the sediment bed at rest and a sequence of images captured during a slow linear flow acceleration (1.3 mm.s-2). As grains begin to move, the correlation drops linearly. Beyond the threshold, the slope of the decorrelation curve diminishes despite the increasing sediment motion. This observation is interpreted as a decorrelation saturation effect. As the bed surface undergoes important restructuring, the image loses its statistical similarity to the reference frame, reaching a correlation floor where further displacements no longer yield a linear decrease in the coefficient.
Generally, overflow flumes are tilted to analyze sediment motion. In this study, the flume slope was kept constant because the image correlation method requires a constant water depth. Consequently, an overflow flume (CH2) was adapted to allow the comparison of thresholds in two different setups. In CH1, the channel is filled until the target water depth is reached. Thus, no additional device is required to control the water height.
The filling process for CH2 differs significantly: it must be progressively filled over 15 minutes before each test to reach the desired water height (Figure 2a). This filling must be performed slowly to prevent premature sediment motion. Therefore, the spillway in CH2 was automated via LabView software to ensure slow filling and to maintain a constant water height.
The main results are summarized below:
- For both S1 and S2, the Ubl values detected in CH2 are lower than those in CH1 (Figure 3). This finding is attributed to step 1 in CH1 which excites the sediment particles and triggers an earlier threshold of motion.
- An overflow flume can be effectively used to determine the threshold motion of sediment particles.
How to cite: Abid, Y., Daich, E., Jarno, A., Benamar, A., and Marin, F.: Adaptation of an overflow flume to study the sediment bedload threshold using image correlation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3481, https://doi.org/10.5194/egusphere-egu26-3481, 2026.
Understanding the impact of flow transients is critical for predicting sediment dynamics in environments characterized by high unsteady currents, such as macro-tidal systems and estuaries. In such contexts, the acceleration and deceleration rates investigated in this study (1.3 to 10.4 mm/s²) provide new insights into how flow unsteadiness affects the sediment transport cycle. The estimation of the threshold motion is very important for the evaluation of sediment transport. The image correlation method developed by Vah et al. (2022) for the detection of threshold motion in laboratory flume is considered. Two thresholds are detected with this method : the bedload (Ubl) and bedform (Ubf) thresholds. They were measured for the sand S328 (D50 = 328 µm) with different acceleration and deceleration ramps.
The stability observed in the threshold of motion for the studied sand can be attributed to an initial triggering of grain movement driven by the instantaneous local drag force. Furthermore, while the bedload threshold remains constant (0.31 m/s) for acceleration rates ranging from 1.3 to 10.4 mm/s², the settling threshold exhibits a strong dependence on flow deceleration. Specifically, at higher deceleration rates, grains maintain motion until reaching lower flow velocities (0.21 m/s), suggesting a significant hysteretic effect driven by particle inertia. Finally, the earlier onset of ripples under high acceleration—occurring at 0.32 m/s compared to 0.36 m/s at lower rates—suggests that fluid acceleration promotes morphological instability, thereby shortening the transition from a flat bed to bedform development.
Reference
Vah, M., Khoury, A., Jarno, A., & Marin, F. (2022). A visual method for threshold detection of sediment motion in a flume experiment without human interference. Earth Surface Processes and Landforms, 47(7), 1778-1789.
How to cite: Daïch, E., Abid, Y., Jarno, A., and Marin, F.: Impact of acceleration and deceleration rates on the entrainment and settling thresholds of a sandy bed, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14789, https://doi.org/10.5194/egusphere-egu26-14789, 2026.
The dynamic motion of submerged flexible vegetation under flow conditions is ubiquitous in aquatic ecosystems. This motion alters flow resistance and affects plant growth, reproduction and evolution. While two-dimensional bending surrogates (e.g., seagrass blades) have been widely used to replicate natural plant motion, vegetation in shallow streams such as ceratophyllum often exhibits complex three-dimensional coherent swaying. Typically growing in gentle, shallow unidirectional flows, such plants rely more on buoyancy than rigidity as an adaptive response—they sway with the flow rather than bend against it.
To testify this hypothesis, we propose a novel non-uniform surrogate conceptualizing such stream vegetation. Laboratory experiments reproduced the three-dimensional coherent swaying behaviour observed in the shallow streams. Results reveal a counterintuitive drag non-increase of the collective coherent swaying in the canopy. A theoretical framework integrates hydrodynamic interactions among flexible plants, sheltering effects, and vortex optimization to explain the observed drag non-increase. Optimal tissue buoyancy, canopy spatial configuration and submergence ratio are derived for the benefit of evolution. The adaptive strategy provides new insights into the trade-offs between rigidity and buoyancy in aquatic vegetation and their implications for canopy function and connectivity.
How to cite: Fu, J., He, G., and Fang, H.: Bending or swaying: adaptive strategy of submerged flexible vegetation in the shallow streams, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17107, https://doi.org/10.5194/egusphere-egu26-17107, 2026.
Coarse sediment transport in Himalayan rivers exerts a first-order control on river morphology, flood hazard, and the longevity of hydropower infrastructure. Variations in gravel or sand export from the mountain front govern downstream channel incision and aggradation rates, directly modifying channel conveyance capacity and flood risk on the Gangetic Plains. These highly mobile gravel-bed rivers draining the Himalayas are prone to abrupt channel switching driven by the mobility of coarse bedload, exacerbating flood hazard. Despite their importance, current flood models and hydropower development plans remain limited by uncertainties in bedload flux estimates.
To understand the controls on sediment yield from the mountain front, we monitor both suspended sediment load through direct sampling, and bedload through acoustic and seismic monitoring at the mountain front of the Karnali and West Rapti Rivers in Nepal. Two Aquarian hydrophones connected to AudioMoth data loggers are installed at each site to monitor bedload transport for the duration of an entire monsoon season. This acoustic dataset is combined with seismic data from a DiGOS geophone at each site, water level data from the Department of Hydrology and Meteorology in Nepal, and manual suspended sediment concentration sampling. These complementary approaches independently approximate the sand and gravel fractions respectively, allowing us to evaluate the accuracy of current approximation methods for bedload in Himalayan rivers.
The results indicate that suspended sediment loads are primarily supply-limited, showing a pronounced seasonal hysteresis in suspended sediment concentration with peaks that record local events such as landslides and storms in the catchment. In contrast, the bedload flux appears to be transport-limited, closely tracking the river discharge. Acoustic data show initial bedload movement at lower discharges, with an abrupt increase in bedload transport signal at a threshold discharge. At higher discharges there is a saturation of the signal, which may reflect boundary conditions of bedload transport or data clipping. These contrasting signals indicate independent transport mechanisms for suspended load and bedload, with a high degree of variability in suspended load relative to a much more predictable bedload flux. Seasonal fluctuations in this bedload-to-suspended-load ratio demonstrate that bedload estimates based on suspended sediment measurements can substantially misrepresent total sediment fluxes, with major implications for flood early warning systems and urban planning.
How to cite: Toro Paz, E., Sinclair, H., Naylor, M., and Gervais, M.: Hydroacoustic insights into bedload and suspended sediment dynamics in Nepal's Himalayan rivers , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19504, https://doi.org/10.5194/egusphere-egu26-19504, 2026.
The Horizontal Acoustic Doppler Current Profiler (H-ADCP), widely used for real-time discharge monitoring, measures flow velocity through the Doppler shift of acoustic pulses. Furthermore, the attenuation and scattering of acoustic waves in water enable the estimation of suspended sediment concentration (SSC), extending its utility from hydrodynamic to sediment monitoring. In Korea, 66 gauging stations equipped with H-ADCPs are currently in operation. By applying sediment estimation techniques based on acoustic backscatters, these systems are expected to enable the simultaneous measurement of both discharge and sediment load. SSC estimation using H-ADCP is based on the linear relationship between SCB(sediment Corrected Backscatters) and individually sampled SSC. Recent studies have attempted to improve the accuracy of SSC estimation by including additional hydraulic and acoustic parameters. In particular, multiple regression models that include water level along with SCB, as well as the attenuation–backscatter ratio (ABR), which jointly accounts for both attenuation and scattering effects, have demonstrated enhanced predictive capability. This study analyzed data from 5 H-ADCP gauging stations to examine the relationships between sediment-related (sediment attenuation coefficient, SCB and ABR) and hydraulic variables (water level, velocity and discharge) using machine learning, aiming to improve accuracy of SSC estimation. The testbeds were equipped with Channel Master H-ADCPs operating at frequencies of 300, 600, and 1200 kHz, and SSC sampling was obtained during the 2024 flood seasons using the D-74 sampler. Using H-ADCPs data and individually measured SSC from the testbeds, both a simple linear regression between SCB and SSC, and a multiple regression including water level were developed and compared against measured SSC. In addition, SSC estimates derived from machine learning models that integrate both hydraulic and acoustic variables were also evaluated for comparison. Application to the testbeds showed that multiple regression including water level improved accuracy compared with simple SCB–SSC linear regression. Furthermore, when machine learning was applied with optimal variable model using diverse variables, the estimation achieved over 85% accuracy relative to individually measured values.
Keywords: SSC, SCB, ABR, water level, H-ADCP
Acknowledgements
This work was supported by Korea Environment Industry & Technology Institute (KEITI) through Research and development on the technology for securing the water resources stability in response to future change Program, funded by Ministry of Climate, Energy, Environment (MCEE) (RS-2024-00397970).
How to cite: Roh, Y., Son, G., and Kim, D.: Continuous Measurement of River Sediment Load Using Acoustic Parameters of H-ADCP, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3248, https://doi.org/10.5194/egusphere-egu26-3248, 2026.
Suspended sediment concentration (SSC) plays a central role in sediment transport, river morphodynamics, ecosystem functioning, and the impact of human activities on fluvial systems. Despite its importance, long-term and spatially distributed SSC monitoring remains limited. Most operational monitoring approaches rely on turbidity as a proxy for SSC, which requires frequent site-specific calibration and often performs poorly when sediment properties vary in time or between catchments. This limits the comparability of measurements across river networks and hydrological conditions.
Here, we present a new approach to in situ SSC monitoring that combines improved optical sensing with a distributed sensor network and embedded data-driven modelling. The monitoring network comprises approximately 20–30 autonomous sensors deployed in Swiss rivers across a range of climatic and geomorphic settings, operated in close collaboration with scientific partners. While the embedded model focuses on improving SSC estimation at the sensor level, the network design enables early network-scale observation of suspended sediment dynamics relevant for morphodynamic analyses.
We introduce an improved optical suspended sediment sensor designed for long-term field deployment. Compared to earlier sensor versions, the instrument shows increased signal stability and sensitivity under variable flow and concentration conditions. A key design feature is access to raw optical measurement signals rather than internally processed turbidity outputs, enabling SSC estimation approaches that are not constrained by traditional turbidity-based assumptions and extending the effective measurement range up to 20 g/L.
Building on this capability, we develop a lightweight embedded machine learning model that estimates SSC directly from raw sensor signals. Instead of using turbidity as an intermediate proxy, the model exploits multi-dimensional signal characteristics that better represent catchment sediment properties. The model is trained and evaluated using paired in situ measurements and reference samples collected across multiple deployment sites.
We assess model performance at selected field sites spanning contrasting hydrological regimes and sediment sources. Results show improved agreement with reference SSC measurements compared to conventional turbidity-based estimates, particularly during periods of rapidly changing sediment concentrations. The approach shows reduced sensitivity to short-term signal variability and sensor drift.
While the network is still at an early stage, these results demonstrate how improved SSC estimation at the sensor level, combined with distributed sensing, can support more transferable observations of sediment dynamics across river systems. The presented framework has implications for sediment transport studies, morphodynamic model calibration and validation, and the design of scalable monitoring networks.
How to cite: Droujko, J.: Beyond turbidity: embedded modelling of suspended sediment concentration and distributed sensing for morphodynamic observation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18817, https://doi.org/10.5194/egusphere-egu26-18817, 2026.
Fluvial suspended sediment is fundamental to channel morphology, delta formation, water quality, biogeochemical cycles and ecosystems. The Earth is currently experiencing unprecedented human impacts and climate change, which are profoundly altering suspended sediment dynamics in river systems. However, fluvial suspended sediment flux (SSF) remains poorly constrained at the global scale, and its response to environmental change is still not well understood. Here, we develop a machine-learning model (XGBoost) to estimate fluvial SSF using in situ observations from 445 gauging stations worldwide, combined with spectral bands and river widths derived from Landsat imagery, river slope from SWOT River Database (SWORD), and bankfull discharge from the Global River Bankfull Discharge (GQBF) dataset (Liu et al., 2024). The trained model is applied to estimate global monthly SSF from 1985 to 2024 for river segments wider than 90 m, covering a total river length of 1.08 × 10⁶ km extracted from the Global River Topology (GRIT) dataset (Wortmann et al., 2024). Independent validation indicates that the model achieves a relative error of 0.12 compared with in situ SSF observations. Our results show that the global average annual SSF is 112.8 kg s⁻¹, with a total sediment delivery from land to ocean of 3705.1 Mt yr⁻¹. From 1985 to 2024, global average annual SSF exhibits a significant decreasing trend (-0.81 kg s⁻¹ yr⁻¹), with an abrupt shift around 2005 from a non-significant to a significant decline (-0.83 kg s⁻¹ yr⁻¹). Despite this global decrease, a larger proportion of river segments show increasing SSF (32%) than decreasing SSF (26%). This apparent contradiction arises because river segments with decreasing SSF typically have higher fluxes (SSF > 50 kg s⁻¹), whereas increasing trends are concentrated in rivers with lower SSF (SSF < 50 kg s⁻¹). Finally, we investigate the dominant drivers and their compounded effects on global fluvial SSF dynamics using a Bayesian network framework. This study provides new insights into global patterns, trends, and controls of fluvial suspended sediment fluxes under ongoing environmental change.
Liu, Y., Wortmann, M., & Slater, L. (2024). Global River BankFull Discharge (GQBF) (0.1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.13855371
Wortmann, M., Slater, L., Hawker, L., Liu, Y., & Neal, J. (2024). Global River Topology (GRIT) vector datasets (0.6) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.11219313
How to cite: Zhou, H., Leyland, J., Darby, S., Tomsett, C., Gernon, T., Hincks, T., and Parsons, D.: Global Patterns, Trends, and Drivers of Fluvial Suspended Sediment Fluxes from 1985 to 2024, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7066, https://doi.org/10.5194/egusphere-egu26-7066, 2026.
This study investigates the propagation and attenuation of short and long waves within mangrove forests by combining physical experiments at the experimental scale with 1D and 2D numerical wave models at the field scale along the Mekong Delta coast. Physical experiments were conducted in a wave flume at TU Delft laboratory to examine the transformation of short and long waves under different mangrove forest configurations. The separation of incident and reflected waves, as well as short- and long-wave components, was performed to quantify the relative contribution of different wave processes to overall wave attenuation. In parallel, numerical wave-flume models were constructed using XBeach and SWASH to mimic the experimental setup. Comparisons between measured and simulated wave parameters indicate a good model performance and support the scaling of experimental findings to real world conditions.
Building on these controlled investigations, the analysis was extended to the Mekong Delta by constructing detailed 1D and 2D numerical models of mangrove forests along the delta's Eastern coast. In addition to real bathymetry, idealised concave and convex cross-shore profiles with varying degrees of curvature were introduced to explore the effect of coastal squeeze and erosion processes on wave transformation. This unified modelling framework enables a systematic comparison of wave behaviour from the laboratory to the field scale. The results demonstrate relatively consistent trends in wave attenuation between physical experiments and numerical models, while also highlighting a strong sensitivity of wave-height transformation to cross-shore profile geometry, mangrove width, and the relative positions of the fish farms. These sensitivities are particularly evident in relation to the location of fish farms and sea dikes situated landward of the mangrove system. Results indicate that a concave profile offers more favorable natural conditions for mangrove development, particularly in terms of wave energy absorption and sediment accumulation, whereas convex profiles are more prone to wave reflection and exhibit lower attenuation efficiency.
The width of the mangrove forest and the location of fish farms or sea dikes landward of the system significantly affect wave-height behaviour both in front of and within the forest. A reduction in mangrove width, together with the landward structures being pushed closer to the shoreline, increases reflected wave energy and return currents at the mangrove edge. Consequently, it is hypothesised that mangrove removal and seaward expansion of fish farms enhance reflected wave heights and return-flow velocities near the forest edge, thereby promoting erosion in this zone. Such processes may induce a transition from convex to concave cross-shore profiles, thereby further accelerating erosion. The results highlight the importance of maintaining sufficient mangrove width and carefully positioning sea dikes and aquaculture infrastructure relative to the mangrove edge, particularly where cross-shore profiles evolve from concave to convex forms that increase wave reflection and reduce attenuation efficiency.
How to cite: Phan, L. K., Vu, A. M., and Stive, M. J. F.: From Physical Experiments to 1D and 2D Numerical Models of Wave Propagation in Mangrove Forests: Implications for Nature-Based Solutions in the Mekong Delta, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16090, https://doi.org/10.5194/egusphere-egu26-16090, 2026.
Mixing processes at the edge of mangrove forests primarily control the exchange of momentum and suspended materials between adjacent channels and the vegetated interior. When a mangrove forest is blocked by sea dikes and fish farms, known as squeeze conditions, the extent of this exchange can change due to stronger velocity gradients and less space for shear-layer development. However, our quantitative understanding of mixing under these squeeze conditions is limited. In this study, particle image velocimetry (PIV) observations and a 2DH model were used to explore mixing at the edge of a squeezed mangrove forest. The goal is to investigate near-edge flow structures that drive lateral exchange and to integrate these processes into eddy viscosity parameters for practical 2DH simulations. A physical experiment in the Delft laboratory flume was performed to examine velocity fields and mixing dynamics at the mangrove edge. PIV was used to measure instantaneous free-surface velocities along the interface, using 2 mm floating tracer particles at 10 Hz for 300 seconds. Results reveal that large horizontal coherent structures (LHCSs), which propagate along the forest edge with cycloidal-like motions, create alternating sweep and ejection events, along with stagnation and reverse-flow phenomena. To simulate the coastal squeeze, the width of the vegetated floodplain (forest) was gradually reduced. PIV data show that LHCSs can influence a larger area inside the vegetation (about 0.40 m) than the mean mixing-layer penetration (about 0.1 m). Reducing the mangrove forest width from 50 cm to 10 cm prevents the mean streamwise velocity from reaching transverse equilibrium, causes peaks in edge Reynolds stress, and shifts dominant quasi 2D structures toward higher-frequency, smaller, and less regular LHCSs (reducing the period from 11.5 to 8.5 seconds and normalised energy from roughly 80% to 65%). These changes hinder lateral exchange and limit conditions for sediment deposition within the forest. Additionally, a depth-averaged 2DH numerical model was created in Delft3D-FLOW to replicate the physical experiment. The simulations successfully captured vortex structures and demonstrated that LHCSs, along with sweep, ejection, stagnation, and reverse-flow events, can be modelled effectively. However, matching the observed magnitude of lateral momentum exchange required employing a hybrid eddy-viscosity model that enhances edge-intensified mixing, which conventional models do not capture. These findings suggest that constructing continuous shore-parallel breakwaters to fully enclose eroding and squeezed mangrove patches in estuarine and open-coast areas could suppress edge-flow events and coherent structures responsible for lateral exchange. This would impede mixing processes essential for mangrove survival and growth.
How to cite: Truong, S. H. and Uijttewaal, W. S. J.: Mixing Processes at the Mangrove Forest Edge under Coastal Squeeze: Insights from PIV and 2DH Modelling for Nature-Based Restoration , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8780, https://doi.org/10.5194/egusphere-egu26-8780, 2026.
The increasing demand for river sediments to meet the needs of rapid urbanization, industrial development, and economic growth has posed significant challenges to several major river systems (Bendixen et al., 2019). Studies have shown that unregulated mining of sand and gravel from rivers can have negative impacts on the morphology, environment, and hydraulic structures located nearby (Rentier and Cammeraat, 2022). The formation of a pit after the extraction of sediment from the river bed is known to influence the local flow and sediment transport processes. These alterations in the hydro-morphodynamic characteristics result in the migration of the mining pit and bed degradation downstream. The advancements in instrumentation and computational modeling techniques have allowed researchers and practitioners to better understand the flow and sediment dynamics near mining locations (Mishra et al., 2024). The literature suggests that the approach used to model mining activities in previous studies generally involved changes to the bed corresponding to the extracted sediment volume at the initial stage. However, in scenarios with in-channel sediment mining activity occurring along with flow over a certain time period, pit formation is gradual (Nguyen et al., 2025). Therefore, in this study, we used the TELEMAC-2D hydrodynamic solver coupled with the GAIA sediment transport model to simulate the impact of gradual mining activity on the hydro-morphodynamics. The results provide insight into sediment transport and bed evolution in the vicinity of the gradual sand extraction site.
References
Bendixen, M., Best, J., Hackney, C., & Iversen, L. L. (2019). Time is running out for sand. Nature, 571(7763), 29-31.
Mishra, R. K., Barman, B., & Pathania, T. (2024). Three-dimensional modeling of hydro-morphodynamic characteristics of mining affected alluvial channel using TELEMAC and GAIA. Physics of Fluids, 36(10).
Nguyen, B. Q., Kantoush, S. A., & Sumi, T. (2025). Assessing the multidimensional impacts of riverbed sand mining on geomorphological change and water transfer rate: A comprehensive investigation of Central Vietnam’s Vu Gia Thu Bon River system. Journal of Hydrology, 654, 132853.
Rentier, E. S., & Cammeraat, L. H. (2022). The environmental impacts of river sand mining. Science of the Total environment, 838, 155877.
How to cite: Mishra, R. K., Barman, B., and Pathania, T.: Numerical Modeling of Gradual Sand Extraction from an Active Alluvial Channel, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16300, https://doi.org/10.5194/egusphere-egu26-16300, 2026.
We perform high-fidelity, two-way coupled simulations to examine sediment transport and flow interactions around a periodic array of seabed-mounted monopiles subjected to oscillatory forcing. The unsteady turbulent flow is resolved by solving the incompressible Navier–Stokes equations, while the evolving sediment bed is modeled using the Exner equation, considering bedload transport as the sole sediment transport mechanism. Bedload fluxes are estimated through empirical correlations calibrated against laboratory experiments and particle-scale simulations. The simulations encompass a range of idealized tidal conditions, including symmetric and asymmetric oscillatory flows and various Shields stress values. Results show that scour evolution is strongly affected by the initial bed topography, flow characteristics, and spatial configuration of the computational domain. Even under symmetric forcing, the sediment bed develops persistent asymmetries and localized deposition near the monopile’s equatorial regions. To enhance predictions of sediment entrainment, we implement a modified erosion-rate model based on a dimensionless shear parameter. The resulting erosion patterns reveal a circular high-entrainment zone around each monopile, consistent with observations from experimental and numerical studies, thereby confirming the model’s physical fidelity and its capability to capture vortex-induced sediment mobilization. In addition, we introduce a post-processing framework to assess hydrodynamic forces on subsea cables. By sampling velocity and pressure fields along hypothetical cable trajectories, this approach enables efficient estimation of force magnitudes and directions for multiple orientations without requiring additional flow simulations.
How to cite: Zgheib, N., Velazquez, I., Krishnaprasad, K. A., Mcghee, C., Ferguson, C., Hoyal, D., and Balachandar, S.: Sediment Erosion around Seabed Structures and Flow-Induced Forces on Subsea Cables, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5, https://doi.org/10.5194/egusphere-egu26-5, 2026.
Hydromorphological processes are fundamental in shaping water bodies, however, predicting erosion, sediment transport and deposition, and their impacts, becomes particularly challenging under extreme conditions. High-magnitude events of anthropogenic or natural origin can trigger the release of massive sediment concentrations into riverine systems, disrupting their equilibrium and driving significant morphological changes on local, regional, short, and long-term scales. Notable examples include debris flows, mass movements, extreme floods, outburst floods, and dam breaks. Among these, tailings dam failures are particularly relevant due to the severe environmental risks they pose in mining regions and the amount of sediment they release. It is evidenced by recent catastrophic events worldwide (Mount Polley in 2014, in Canada in; Mariana in 2015 and Brumadinho in 2019, in Brazil), that caused severe and long-lasting damage to ecosystems, river systems, and communities. In this context, a significant scientific gap remains in understanding how numerical sediment transport models perform under such conditions. Most sediment transport equations are empirical and were originally developed for natural river ecosystems. They were not built for the hyper-concentrated flows associated with catastrophic flood events, like extreme floods and tailings dam breaks. Consequently, assessing the efficacy and sensitivity of hydrodynamic models coupled with sediment transport for extreme events becomes an important step to evaluate viable tools for impact assessment and prognostic evaluations. In this study, we evaluated a physically-based 2D hydrodynamic model (HEC-RAS 2D) to simulate the sediment dynamics of the 2019 Brumadinho dam break in Brazil. During this event, approximately 9.8 Mm³ of material was released in just 5 minutes. The tailings wave, consisting of 45% sediment particles, propagated downstream in a small subcatchment (Ferro-Carvão stream) for 20 km over approximately 1.5 hours until reaching a major river. It is estimated that nearly half of the released volume was retained in the Ferro-Carvão floodplain through depositional processes, flooding 2.7 km² and significantly reshaping the local morphology. A global sensitivity analysis was performed using a Monte Carlo framework, generating 630 model runs that varied four key sediment-related input parameters: total sediment load, grain size distribution, sediment specific gravity, and model adaptation length. The methodology integrated validation with observed field data, sediment mass balance, and non-parametric statistical tests (Kruskal–Wallis) to assess parameter significance across outputs such as bed change, sediment mass outflow, and volume in the model’s domain. Results show that sediment load strongly influenced all outputs (bed change, sediment outflow, and volume outflow), while specific gravity and adaptation length had moderate effects, particularly on depositional patterns. Grain size showed unexpectedly low sensitivity. Validation results demonstrated model reliability in simulating the case study, with relative errors ranging from 8.1% to 10.1% and accuracy rates of 90–92% for bed change, sediment outflow, and volume outflow. The simulation effectively reproduced spatial sediment dynamics, with depositional zones matching field observations. However, localized overestimations of deposition highlighted limitations in capturing specific erosional processes. These findings underscore the importance of sensitivity analysis for robust calibration and provide critical insights into the uncertainties of simulating morphological changes driven by extreme events.
How to cite: Mello, C. and Eleutério, J.: Capability of hydrodynamic model to achieve sediment transport and deposition dynamics for large flood events: a parameter sensitivity analysis for a tailings dam break real event, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14817, https://doi.org/10.5194/egusphere-egu26-14817, 2026.
Soil erosion is a significant environmental issue with far-reaching consequences for both agriculture and the natural ecosystem. Soil water repellency (SWR) impacts erosion through a dual mechanism. Hydrologically, SWR reduces infiltration and enhances overland flow, intensifying erosion. Mechanically, it affects soil cohesion, potentially decreasing resistance to detachment. While the hydrological effects are well studied, the mechanical impacts of SWR remain less explored. Previous studies have reported mixed impacts of SWR on soil erosion, with SWR sometimes increasing soil erosion and, in other cases, reducing it. To address this apparent ambiguity, we use catchment-scale simulations with the LISEM model to systematically isolate and test SWR’s hydrological effects (via reduced infiltration) and mechanical effects (via altered soil cohesion) on erosion. Two types of configurations are considered: spatially homogeneous (uniform land cover and soil type) and heterogeneous (spatially varied SWR, based on land cover or soil type). All configurations are run under two regimes: low- and high-excess rainfall. Considering only the hydrological impacts was found to consistently increase erosion in all configurations. In homogeneous setups, changes in soil cohesion produce texture-dependent responses: increased soil cohesion mitigates erosion increases in finer soils but has a limited impact in coarse-textured soils. This effect is much more pronounced under high-excess rainfall than low-excess rainfall. The heterogeneous configuration exhibits distinct spatial patterns: land cover–based heterogeneity follows vegetation-slope interactions, whereas soil-based heterogeneity is shaped by intrinsic soil hydraulic–-mechanical properties. Overall, the net erosional impacts of SWR are shown to depend on the balance between its hydrological and mechanical effects on erosion. This research implies that preventing and mitigating the erosional impacts of SWR requires a management approach adapted to the prevailing land-use and soil conditions.
How to cite: Van De Wiel, M. and Fallah, T.: Modelling the Impact of Soil Water Repellency on Catchment-Scale Soil Erosion, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14471, https://doi.org/10.5194/egusphere-egu26-14471, 2026.
Reservoir sedimentation is the gradual deposition of sediment transported by inflowing rivers in artificial lakes. Monitoring this accumulation is essential to preserve storage volume and protect infrastructure, such as turbine components. Numerical models are powerful tools to address this goal, as they can simulate morphodynamic processes across both temporal and spatial scales. In this study, we developed a Delft3D-FM model of Lake Seminole (USA) to answer two questions: (1) how does deposition change between regular flow and flood conditions? and (2) what is the impact of upstream flow regulation on sediment deposition?
Created in 1954 with the construction of the Jim Woodruff Dam, Lake Seminole sits at the confluence of the Chattahoochee and Flint rivers. This location is an ideal site because the reservoir is divided into two distinct arms:
- The Chattahoochee arm, which is fed by the heavily regulated Chattahoochee River and experiences strong daily discharge fluctuations due to hydropeaking.
- The Flint arm, which is fed by the minimally regulated Flint River and exhibits a natural flow regime.
Here we develop a morphodynamic Delft3D-FM model coupled with the Real-Time Control (RTC) module. Time-variable discharge inputs from USGS gauges define the upstream boundary conditions, while water levels at the dam define the downstream boundary. The hydrodynamic model is calibrated using OpenDA by adjusting Manning’s roughness coefficients based on Signature 1000 ADCP velocity measurements. The sediment transport model is calibrated using suspended sediment concentrations collected via Teledyne ISCO water samplers.
Model results show that regular flow conditions lead to net deposition, while flood conditions generate temporary and deep scouring, resulting in net erosion. Additionally, in the Chattahoochee arm, daily discharge fluctuations driven by hydropower redistribute fine sediments throughout the reservoir during peak flows. As discharge drops, sediments settle but are quickly remobilized by the subsequent peak flows. Overall, this study illustrates how hydraulic conditions drive morphological change in Lake Seminole and underscores the significant impact of river regulation on reservoir sedimentation.
How to cite: Cortese, L., Behn, M., Edgington, A., Crisanti, S., Dahl, T., Sheehan, C., Tarpley, D., Tritinger, A., and Snyder, N.: Modelling the Morphodynamic Response To Flow Regulation In An Artificial Reservoir, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13816, https://doi.org/10.5194/egusphere-egu26-13816, 2026.
In cold regions, river sediment transport during mid-winter periods is strongly influenced by the presence of ice cover. However, the effects of ice cover on bed shear stress, sediment mobility, and the longer-term evolution of fluvial geomorphology remain insufficiently understood due to the complexity of the physical mechanisms and the scarcity of relevant field measurements. To address this gap, the present study investigates mid-winter bedload transport processes in a sub-arctic river under ice-covered conditions using the Delft3D Flexible Mesh (Delft3D FM) software. The modelling approach employs a novel integration of three-dimensional (3D) hydrodynamics, sediment transport and ice to resolve interactions between hydraulics, ice-induced resistance, and sediment mobility. The Pulmankijoki River in northern Finland was selected as the study site owing to its typical sub-arctic hydrological regime and seasonal ice cover. Comprehensive field measurements, including river topography, flow discharge, water level, sediment diameters, bedload transport rate, and ice thickness, were conducted during 22–29 February 2022, 21–28 February 2023, and 17–24 February 2024.
Based on the numerical results, firstly, comparison with field measurements shows that the 3D model is more accurate than the depth-averaged (2D) approach, demonstrating its advantage in bedload transport simulations under ice-covered conditions. This highlights the importance of resolving vertical velocity gradients. Secondly, sensitivity experiments on the ice-cover roughness coefficient indicate that ice roughness has only a minor influence on bed shear stress and therefore does not significantly modify bedload transport rates. Thirdly, by mapping the ratio of local bed shear stress to critical shear stress, spatial patterns of sediment transport potential during the three mid-winter seasons were clarified, illustrating how sediment mobility persists beneath ice. This study demonstrates that Delft3D FM is an effective modelling tool for resolving sediment transport under ice-covered conditions in sub-arctic rivers. The findings contribute to an improved process-based understanding of winter river dynamics and provide insights for sediment management strategies in cold-region environments.
How to cite: Ding, C., Saberi, O., Takala, T., Välimäki, J.-M., de Goede, E., Jagers, B., Mosselman, E., and Lotsari, E.: Ice‐covered river hydraulics and bedload transport: Insights from three-dimensional modelling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11709, https://doi.org/10.5194/egusphere-egu26-11709, 2026.
Suspended sediment transport in natural and engineered aquatic systems is often governed by the settling behavior of porous and permeable particles such as flocs, aggregates, and organic-rich sediments. Understanding how particle permeability influences hindered settling is therefore essential for predicting sediment residence times, vertical fluxes, and deposition rates in rivers, lakes, and reservoirs. We investigate the settling dynamics of suspensions of highly porous and permeable particles using particle-resolved direct numerical simulations in the viscously dominated regime. The simulations employ a coupled Euler–Lagrange framework that explicitly accounts for particle permeability, allowing us to systematically quantify bulk settling velocities as a function of particle permeability and particle volume fraction. Our results show that the bulk settling velocity follows the classical Richardson–Zaki power-law scaling with volume fraction, but that particle permeability significantly modifies hindered settling. Suspensions composed of more permeable particles settle substantially faster at increasing concentrations: at a particle volume fraction of 30%, the bulk settling velocity differs by up to 116% between the least and most permeable particles considered. This enhanced settling is explained by permeability-dependent modifications of the fluid counterflows induced by particle displacement. Quantitative analysis of the mean vertical fluid velocity demonstrates that more permeable particles generate weaker upward counterflows, thereby reducing hydrodynamic resistance to settling. We further examine how velocity fluctuations, particle self-diffusivity, and suspension microstructure depend on particle permeability and concentration. Velocity fluctuations increase systematically with particle volume fraction and are strongest for the least permeable particles. Analysis of Voronoï tessellation and pairwise particle distributions reveals pronounced permeability-dependent microstructural differences, with stronger clustering and broader Voronoï cell volume distributions at low permeability, attributed to enhanced lubrication forces. In contrast, higher permeability leads to a greater likelihood of close particle proximity due to weakened interparticle pressure effects. These findings highlight particle permeability as a key control on hindered settling and suspension structure, with direct implications for process-based numerical models of sediment transport and deposition in open water environments.
How to cite: Vowinckel, B. and Metelkin, A.: Highly-resolved simualtions of hindered settling of porous particles, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3496, https://doi.org/10.5194/egusphere-egu26-3496, 2026.
Understanding the size distribution of soil particles is very important for predicting how both sediment and agricultural chemicals move through the environment. However, most erosion models are limited because they only use a few broad size groups. While the Hairsine-Rose (HR) model can handle many different sizes, there is a trade-off between having a large number of size classes for accuracy, versus a smaller number for computational efficiency. There is very little, if any, discussion in the literature about how many size classes are needed, or how fall velocities should be chosen to reliably represent the corresponding size class ranges.
We address both these questions through developing a model for a continuous, rather than the commonly used discrete settling velocity distribution. By integrating over discrete ranges of the settling velocity distribution, an equivalent discrete model can be obtained. This then provides conditions on how the discrete settling velocities need to be chosen in order to minimise the associated error in representing the overall distribution. We then show how this error varies under both steady and unsteady flow conditions.
How to cite: Ramezani Lashkariani, M. and Sander, G.: Sediment Transport In Shallow Overland flow, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20439, https://doi.org/10.5194/egusphere-egu26-20439, 2026.
In rivers, marshes, and mangroves, dense vegetation is a ubiquitous, but complex, obstruction to flow, demanding special consideration of its effect on hydromorphological processes. The last twenty-five years have seen a range of studies on different aspects of flow-vegetation interaction, but to properly understand the impact of foliated, heterogeneous, and branching plants, it is necessary to adopt three-dimensional structural modelling techniques to quantify their hydrodynamic interactions. We apply the recently developed Elastically Articulated Body Method (EABM), which describes the three-dimensional dynamics of complex plant morphologies to investigate the flow-induced reconfiguration of leafy plants (such as Ceratophyllum, Suaeda, and Spartina). Our results show that the dynamics and hydraulic effects of different plant species, for instance those that can be used as nature-based solutions for coastal protection, can be classified using a new dimensionless parameter “Isoanemeity”. This parameter is a descriptor of the ability of leaves to flexibly streamline, compared to that of the whole plant, and as such predicts the predominant mechanism of plant reconfiguration, and the role of foliage in creating drag. This classification can benefit those modelling drag and turbulence in large hydrological systems with a variety of species of vegetation.
How to cite: Dickinson, R., Marjoribanks, T., and Keylock, C.: Classifying Foliated Ecohydraulics via Three-Dimensional Modelling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2546, https://doi.org/10.5194/egusphere-egu26-2546, 2026.
Erosion of hydraulic concrete induced by submerged sediment-laden jets constitutes a representative surface damage problem that is strongly governed by physical processes while exhibiting limited textural contrast, representing a multiphase sediment-structure interaction process relevant to sediment management and operation-maintenance of hydropower infrastructure. Its spatial heterogeneity and graded erosion patterns arise from the coupled effects of sediment momentum transfer and erosion evolution. Conventional erosion assessments predominantly rely on integral metrics such as mass or volume loss, which are insufficient to describe the two-dimensional spatial structure and graded characteristics of erosion damage. These erosion patterns represent a localized surface-morphological response of hydraulic concrete surfaces in sediment-laden jet environments. Although computer vision techniques have recently been applied to erosion detection, existing approaches remain largely texture-driven and data-centric, typically focusing on binary segmentation between damaged and undamaged regions. Such models are therefore inadequate for resolving multiple erosion grades and lack explicit incorporation of erosion mechanisms, leading to limited robustness and interpretability across varying hydraulic and sediment conditions. In this work, a physics-informed computer vision (PICV) framework is developed for intelligent segmentation of hydraulic concrete erosion, bridging mechanism-based sediment action modelling with data-driven image segmentation. The framework is built upon a structured physical-visual representation that explicitly links erosion morphology with sediment-induced physical actions. Controlled submerged sediment-laden jet experiments are conducted under systematically varied jet velocities, impingement angles, sediment concentrations, particle sizes, and exposure durations to acquire high-resolution erosion surface images. Based on particle impact and cutting mechanisms, spatially distributed sediment-phase momentum fields, including normal and tangential components, are derived to characterize the intensity of particle-wall interactions, serving as modelling-informed multiphase sediment action descriptors. These momentum fields are spatially registered to the corresponding erosion images, forming a coupled two-dimensional representation in which erosion surface images serve as the visual carrier and are associated with aligned physical descriptors. This representation provides a physics-vision integrated dataset suitable for mechanism-aware visual learning. On the basis of this coupled representation, a PICV-oriented multi-modal segmentation framework is established, in which erosion images and sediment momentum fields are jointly exploited to enable concurrent learning of textural features and physically meaningful action intensity. Furthermore, a dimensionless erosion intensity indicator derived from experimentally measured mass loss rates is incorporated into the loss function as a soft-consistency regularization term, providing sample-wise adaptive guidance during model optimization. Rather than imposing strict physical constraints on the solution space, physical information is used to guide the learning process toward physically plausible spatial patterns. Compared with image-only baselines (U-Net and DeepLab), the proposed PICV model improves multi-class graded-segmentation performance (Pixel-wise precision: +10-15 percentage points) and notably reduces grade confusion in transition regions. Under cross-condition evaluation, PICV demonstrates enhanced stability and interpretability, linking predicted grade distributions to aligned momentum patterns. This framework provides a transferable pathway for robust, mechanism-aware erosion assessment under complex submerged sediment-laden jet environments, supporting erosion-risk evaluation and sediment-management decision-making for hydraulic infrastructure.
How to cite: Cai, M., Wang, H., Liu, K., Chen, Y., and Liu, Z.: A physics-informed computer vision framework for graded erosion processes of hydraulic concrete under submerged sediment-laden jets, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2368, https://doi.org/10.5194/egusphere-egu26-2368, 2026.
How to cite: Son, G., Kwak, S., and Roh, Y.: Size-Dependent Measurement Variability in LISST-200X–Derived Suspended Sediment Particle Size Distributions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3239, https://doi.org/10.5194/egusphere-egu26-3239, 2026.
Suspended sediment data are essential for hydrological and water resource management, including predicting riverbed changes, estimating reservoir sedimentation, calculating sediment yield, and supporting river management planning. Suspended sediment also causes turbidity, which complicates water treatment and negatively impacts aquatic ecosystems. These issues highlight the need for precise and continuous monitoring. Although long-term monitoring and research on sediment transport have been conducted worldwide for decades, Korea still lacks sufficient systematic, long-term datasets and technological development, resulting in a shortage of usable information. Conventional samplers such as the D-74 and P-61 face limitations in field application due to the need for multiple personnel, high costs, safety risks, and accessibility constraints. Moreover, indirect methods such as ADCP backscatter and LISST diffraction still require further validation with ground truth data.
To address these limitations, we developed a pumping-based automated sampling system and evaluated its field applicability in a small- to medium-sized river in Korea. The system was installed at a field site in Yeoju, Korea, across three cross-sections, with a total of 16 intake ports distributed at 5–6 depths per cross-section to enable automated multi-depth sampling under varying stage conditions. A joint field campaign, conducted alongside ADCP, LISST, conventional samplers, and surface grab sampling, provided comparative measurements for suspended-sediment characterization and sediment-load estimation. The system operated stably over water-level fluctuations and produced reproducible samples, indicating strong potential for safer and more efficient long-term monitoring.
In conclusion, this study demonstrates that the pumping-based automatic sampler can serve as a practical alternative to conventional suspended sediment measurement methods. The system reduces safety risks, labor, and costs while enabling multi-depth and multi-cross-sectional sampling, thereby providing more accurate suspended sediment distribution and total load estimation. Beyond its application in small- and medium-sized rivers, this approach has the potential to be extended to larger rivers and diverse hydrological conditions, offering a robust technical foundation for advancing suspended-sediment monitoring programs.
This work was supported by Korea Environment Industry & Technology Institute (KEITI) through Research and development on the technology for securing the water resources stability in response to future change Program, funded by Ministry of Climate, Energy, Environment (MCEE) (RS-2024-00397970).
How to cite: Kwak, S., Son, G., and Roh, Y.: Field Evaluation of a Pumping-Based Automated Sampler for Suspended-Sediment Monitoring in Small to Medium Rivers, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3260, https://doi.org/10.5194/egusphere-egu26-3260, 2026.
Debris-flow avulsion controls the shifting of active flow pathways across an alluvial fan and strongly influences fan construction. In turn, fan morphology and its evolution are major factors governing where avulsion occurs. Yet the avulsion process exhibits strong uncertainty and stochastic behavior that remains poorly resolved in field records. Most existing datasets are restricted to event- or annual-scale observations and therefore lack the temporal resolution needed to quantify how channels relocate during an event.
This study introduces a laboratory framework that directly resolves debris-flow avulsion using high-frequency topographic data. Debris flows built an alluvial fan within a 60 × 90 cm basin while eight synchronized 2K industrial cameras captured continuous multi-view imagery for Structure-from-Motion reconstruction. Spatial targets and an automated workflow yielded sequential point clouds, orthophotos, and DEMs in a fixed coordinate system, resolving fan-surface evolution at 0.1-s intervals and capturing rapid adjustments associated with avulsion.
We also obtain a consistent space–time record of channel traces during fan building, allowing relocation to be tracked at sub-second intervals. This record is derived by applying short-window long-exposure stacking to successive image frames, where locally disturbed areas reveal instantaneous channel footprints.
The resulting database captures sub-event-scale coupling between avulsion and fan morphology, clarifying how avulsion both responds to and reorganizes the fan surface. It also enables direct quantification of avulsion geometry, recurrence, and lateral displacement. Building on the empirical constraints provided by these measurements, the study aims to formulate a stochastic framework based on Gamma-subordinated OU processes to represent the episodic and bounded properties of debris-flow avulsion and to assess their implications for long-term fan morphology.
Figure. High-frequency SfM measurements of alluvial-fan evolution.
Top row: DEMs; middle row: orthophotos; bottom row: channel footprints extracted by short-window long-exposure stacking, revealing debris-flow avulsion.
How to cite: Tsai, I.-W. and Chen, T.-Y. K.: Resolving Debris-Flow Avulsion Using Sub-Second Laboratory Topographic Time Series, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3406, https://doi.org/10.5194/egusphere-egu26-3406, 2026.
We report laboratory experiments devoted to the morphodynamics of fluvial deltas. Along the topsets of the prograding deltas, we observe the formation and upstream migration of cyclic steps and hydraulic jumps. The hydraulic jumps exert key controls on the cyclic step morphology, curtailing bed erosion by decelerating the flow and also delaying redeposition by mixing the suspended sediment throughout the flow depth. To characterize the associated water flow, sediment transport, and bed evolution, we image the backlit channel through its transparent sidewalls. A wide-angle camera records the cyclic steps and hydraulic jumps at regular time intervals, yielding repeat measurements of the slowly evolving sediment bed and free surface profiles (Fig. 1). In parallel, a high-speed camera records the rapid flow of suspended sediment particles through the jump (Fig. 2). Velocity and sediment concentration profiles are extracted, to characterize the mixing processes and energy dissipation that occur in the jump region. To complement the experimental measurements, the results of preliminary modeling attempts will also be reported.
Keywords: delta long profile evolution; cyclic steps; hydraulic jumps over erodible beds.
Fig. 1 Side view of the constant-width experimental channel, showing the formation of cyclic steps along the delta topset.
Fig. 2 High-speed visualization of the toe of the hydraulic jump: (a) Raw image frame; (b) Measured velocity field, with velocity profiles (orange) and sediment bed (red), zero horizontal velocity (green), and water free surface profiles (blue).
How to cite: Liao, B.-Z. J., Su, C.-C., Ni, W.-J., and Capart, H.: Cyclic steps and hydraulic jumps along the topsets of experimental deltas, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4178, https://doi.org/10.5194/egusphere-egu26-4178, 2026.
We describe the development of a multi-camera system tailored for small-scale hydrodynamic and morphodynamic experiments. The system includes four precisely synchronized stationary cameras, together with a laser scan traverse. Prior to water flow, this allows precise camera calibration and topography measurements. The calibrated cameras are then used to acquire stereo views of the flow free surface (Fig.1), seeded with fluorescent particles (to avoid light reflection). The 3D positions of the particles are determined to sub-millimeter accuracy, and their trajectories obtained by particle tracking (Fig.2). This allows measurements of channel topography, surface topography and surface velocity to be acquired in a common frame of reference. The methods are validated using pure water flows over 3D-printed topography, then applied to experiments involving flows past live sediment beds, including debris fans and slackwater deposits. In addition to measurements, preliminary comparisons with hydrodynamic model results will also be reported.
Keywords: multi-camera imaging; stereo imaging; three-dimensional topography and velocity measurements.
Fig.1 Flood flow past a debris flow fan in a small-scale laboratory channel, stereoscopic views.
Fig.2 Flood flow past a debris flow fan in a small-scale laboratory channel. Top: surface velocity map (up to 60 cm/s); bottom: particle trajectories.
How to cite: Zhou, E. D.-X., Chiu, T.-H. L., Ni, W.-J., and Capart, H.: Multi-camera measurements of free surface topography and velocity for water flows past sediment deposits, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4231, https://doi.org/10.5194/egusphere-egu26-4231, 2026.
Accurate experimental characterization of velocity profiles in open-channel flows is essential for hydraulic research and field-scale monitoring; however, the performance of Acoustic Doppler Current Profilers (ADCPs) near flow boundaries remains insufficiently constrained due to acoustic blind zones and instrument-induced biases. This contribution presents a comprehensive multi-method validation framework combining laboratory-scale Particle Image Velocimetry (PIV), ADCP measurements, and Computational Fluid Dynamics (CFD) simulations to quantify ADCP accuracy and limitations under controlled conditions.
Initial experiments were conducted in a straight rectangular flume under six steady flow conditions spanning Reynolds numbers from 6.5 × 10⁴ to 1.76 × 10⁵. High-resolution 2D2C-PIV provided near-wall velocity measurements with millimeter-scale spatial resolution and served as the primary experimental reference. ADCP measurements were obtained using a 3 MHz profiler (RS5). Validated CFD simulations reproduced the mean velocity profiles across the full flow depth and were used to complement regions inaccessible to acoustic measurements.
Results show that ADCP-derived mean velocities agree well with both PIV and CFD in the core flow region, with typical deviations within ±3–5%. Larger discrepancies occur in the lower and upper parts of the water column, where ADCP velocities exhibit depth-dependent measurement bias of up to 25–30% at low Reynolds numbers, associated with blanking distance, reduced signal correlation, and side-lobe interference. A tendency toward reduced velocity discrepancies with increasing Reynolds number is observed in the lower part of the water column, although the trend is not strictly monotonic across all flow cases. Consistent agreement between PIV and CFD confirms that the observed deviations primarily arise from instrumental limitations rather than flow physics. Building on these validated results, ongoing work focuses on optimizing ADCP configuration parameters, developing CFD- and PIV-assisted blind-zone reconstruction strategies, and extending the framework toward instrument-aware CFD and field-scale applications. The study establishes a reproducible benchmark for ADCP validation and provides practical guidance for interpreting acoustic velocity measurements in laboratory and natural open-channel flows.
How to cite: Tuhin, M. T. H., Ladwig, M., Razzaq, M., Zirngibl, F. B., Gradzki, D. P., Gurris, M., Lindken, R., Hinkelmann, R., and Mudersbach, C.: Validation of ADCP Velocity Measurements in Open-Channel Flow Using PIV and CFD, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7466, https://doi.org/10.5194/egusphere-egu26-7466, 2026.
Floating debris accumulation in rivers is a critical hydraulic and geomorphological concern, especially during floods when large volumes of debris are mobilized and conveyed downstream (Pace et al., 2024). Debris accumulation at hydraulic structures (e.g., bridges and weirs) can markedly increase flow resistance, intensify local acceleration and turbulence, and impose excessive hydrodynamic loads, thereby threatening structural integrity and flood safety (Diehl, 1997; Ruiz-Villanueva et al., 2016). Despite numerous flood-related failures associated with floating debris , the three-dimensional processes governing debris accumulation and its interaction with complex flow fields remain insufficiently understood, limiting robust prediction and risk assessment (Braudrick and Grant, 2000; Manners et al., 2007). This study develops an open-source, three-dimensional numerical model(OpenFOAM) informed by flume experiments and elucidates the hydraulic mechanisms underlying floating debris accumulation through quantitative validation against laboratory observations.
The model incorporates experimentally observed debris-accumulation configurations and hydraulic responses (Kim, 2021; Müller et al., 2022), and reproduces debris transport pathways and accumulation processes based on controlled debris-feeding experiments (Toé et al., 2025). Model performance is evaluated across multiple accumulation scenarios through quantitative comparisons of key hydraulic variables, including water surface elevation, velocity fields, and Froude number, enabling assessment of backwater effects, local flow acceleration, and flow-regime transitions. In addition, the stability and failure of debris carpets reported by Toé et al. (2025) are numerically reproduced to examine accumulation–flow feedbacks under increasing discharge. The results demonstrate that the proposed model successfully captures the fundamental hydraulic processes governing floating debris accumulation and provides a robust framework for analyzing debris–flow interactions at hydraulic structures.
Numerical predictions agree closely with experimental measurements, demonstrating that the model captures fundamental hydraulic mechanisms controlling debris accumulation at structures. The simulations reproduce preferential accumulation zones and temporal growth rates, resolving the coupling between three-dimensional flow structures and debris transport. Results further show that accumulation-induced flow contraction and associated near-bed shear stress amplification intensify localized turbulence and modify the near-bed flow regime, which in turn governs accumulation stability. Importantly, the spatial distribution and magnitude of bed shear stress emerge as primary determinants of transitions from stable accumulation to instability (e.g., squeezing) and eventual failure.
The proposed, experimentally validated, physics-informed model provides a reference framework for simulating floating debris transport, accumulation dynamics, and interactions with hydraulic structures. It supports quantitative assessment of debris-induced head losses and hydraulic loads, thereby informing flood-risk evaluation and the design and management of debris-prone structures.
”This work is financially supported by Korea Ministry of Climate, Energy, Environment (MCEE) as ｢Research and Development on the Technology for Securing the Water Resources Stability in Response to Future Change (RS-2024-00332494)｣.”
How to cite: Kim, J. and Kang, H.: Three-Dimensional OpenFOAM-Based Simulation of Floating debris Transport and Accumulation at Hydraulic Structures, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8837, https://doi.org/10.5194/egusphere-egu26-8837, 2026.
Vegetation can substantially alter flow behavior in streams by increasing hydraulic resistance, modifying momentum exchange, and generating localized flow structures. In two-dimensional flow modeling, representing vegetation effects remains challenging because model setups typically require estimating multiple spatially distributed resistance parameters from vegetation patterns and parameterizing heterogeneous vegetation traits. Among these, the flow-resistance coefficient for the vegetated section is the most sensitive yet uncertain parameter, and it is frequently simplified or assigned empirically. Therefore, this study investigates the sensitivity of two-dimensional model predictions of water-surface elevation and velocity to the flow-resistance coefficient in a vegetated channel.
Numerical simulations were performed using HEC-RAS 2D and calibrated against a large-scale flume experiment conducted in a straight channel with evenly spaced willow patches along the centerline. Channel topography was reconstructed from high-density point-cloud data and resampled into digital elevation model datasets at a 1 mm grid resolution. The vegetated channel was simulated under both high- and low-flow conditions using three vegetation patch configurations: group-dense, single-dense, and single-sparse. Flow resistance within the vegetated areas was represented by spatially distributed Manning’s n values in the HEC-RAS 2D model. Model results obtained using Manning’s n values derived from a momentum-based model were compared with those obtained using manually calibrated Manning’s n values.
The results show that, for the group-dense configuration, applying Manning’s n values estimated by the momentum-based model led to overestimation of both water-surface elevation and flow velocity relative to the large-scale experiment data. Manning’s n values manually calibrated to match the experimental observations were lower than those estimated by the momentum-based model. For the single-patch configurations, both dense and sparse cases consistently underestimated water-surface elevation, whereas flow velocities were overestimated across all tested Manning’s n values. Overall, the study shows that the performance of vegetation-related Manning’s n in two-dimensional hydraulic models varies with vegetation density and patch configuration. The observed differences between group and single-patch vegetation highlight potential limitations in representing vegetation resistance solely through a Manning’s n parameter under spatially heterogeneous conditions.
Acknowledgement: This research was funded by the Korea Environment Industry & Technology Institute (KEITI) through the Smart Water-supply Service Research Program, funded by the Korea Ministry of Climate, Energy, Environment (MCEE)(RS-2022-KE002091).
How to cite: Haque, L. F. S., Jang, E., and Ji, U.: Sensitivity of HEC-RAS 2D Predictions to Vegetation-Related Manning’s n in Patchy Vegetated Channels, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16533, https://doi.org/10.5194/egusphere-egu26-16533, 2026.
Two different optical sensors were used to investigate the relationship between the grain size of suspended sediment and turbidity readings. Turbidity measurements are frequently used in practice to assess sediment transport in water bodies. If the influence of grain size on turbidity sensor readings is ignored or insufficiently addressed, the estimated sediment concentrations and, consequently, sediment amounts can be biased. This contribution presents laboratory results from an experiment on the dependence of turbidity readings on different grain size and concentration regimes. The importance of grain size is demonstrated using three wide grain-size range sediment suspensions and seven narrow grain-size sediment suspensions. Additionally, the findings were applied to a real-life example to illustrate how misleading “simplified” sediment rating curves can be when assessing sediment load.
How to cite: Lebar, K., Rusjan, S., and Kuzmanić, T.: Grain size controls on turbidity-based suspended sediment estimation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17138, https://doi.org/10.5194/egusphere-egu26-17138, 2026.
The objective of this contribution is to assess the applicability of an Acoustic Doppler Current Profilers (ADCP) system for open-channel velocity measurements through validation against Stereoscopic Particle Image Velocimetry (Stereo-PIV) data. Stereo-PIV provides high spatial resolution and detailed insight into flow structures in laboratory open-channel hydraulics, delivering three-dimensional velocity components. ADCPs are widely used for velocity and discharge measurements, offering robust data collection even in sediment-laden and optically challenging environments. Their performance depends on acoustic frequency, flow conditions, and the size and concentration of suspended particles. To evaluate both systems under identical conditions, we conducted simultaneous Stereo-PIV and ADCP measurements in a laboratory flume, with emphasis on acoustically challenging regions.
In this contribution, we present results from measurements conducted in a 16 m open-channel flume with a rectangular cross-section at the Laboratory for Hydraulic Engineering and Hydromechanics at Bochum University of Applied Sciences. The experiments covered Reynolds numbers between Re = 4.6 × 10⁴ and 1.6 × 10⁵ and Froude numbers between Fr = 0.04 and 0.1. The stereoscopic PIV setup consists of two CMOS double-frame cameras with macro lenses and Scheimpflug adapters. Polyamide (PA12) particles with a mean size of 20 µm were used as tracers and were illuminated by a Nd:YAG double-pulse laser. Stereo-PIV measurements were performed in a cross-sectional plane oriented orthogonal to the side walls. Measurements at multiple streamwise positions were obtained by translating the plane in several equidistant increments, enabling the assessment of spatial variations along a defined channel segment. For the ADCP measurements a Sontek RS5 profiler was used under clear-water conditions to capture velocity profiles in the fully developed flow region. The analysis accounts for near-boundary limitations by focusing on ADCP blanking zones and their impact on mean velocities and turbulence proxies.
Results show a high accuracy of the Stereo-PIV and ADCP measurement in the core region of the channel flow with slight deviations in the measurement results and to theory. Closer to the boundaries the ADCP results deviate stronger from the Stereo-PIV results, indicating the need to optimize the ADCP evaluation methods for near-boundary applications.
How to cite: Zirngibl, F. B., Ladwig, M., Tuhin, M. T. H., Gradzki, D. P., Mudersbach, C., and Lindken, R.: Stereo-PIV-based assessment of ADCP performance in turbulent open-channel flow, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18596, https://doi.org/10.5194/egusphere-egu26-18596, 2026.
Hydrological models such as HEC-RAS are widely used for flood hazard mapping, but translating these hydraulic outputs into spatially explicit bank erosion risk maps remains challenging. This difficulty arises primarily from the lack of sedimentological data and the highly localized nature of bank erosion during flash floods. Machine learning (ML) offers a powerful tool to uncover complex, non-linear relationships between hydraulic parameters and observed erosion patterns. This study aims to develop and validate a logistic Generalized Additive Model (GAM) that predicts the probability of bank erosion using hydraulic parameters derived from HEC-RAS simulations (e.g., flow velocity, bed shear stress). The model is calibrated and validated using erosion maps derived from high-resolution LiDAR-based elevation change detection. To assess real-world applicability, we validate model predictions against field survey data from the 2021 Ahr flood, providing ground-truthed erosion locations for independent evaluation beyond LiDAR-based mapping.
To quantify the spatial relationship between hydraulic conditions and observed bank erosion, we implemented a two-step workflow combining hydraulic modeling and remote sensing-based erosion mapping. First, we performed a 2D hydrodynamic simulation of the Ahr catchment using HEC-RAS v6.6, driven by a high-resolution 5-m digital elevation model (DEM) and precipitation input derived from the RADOLAN dataset for the extreme July 2021 flood event. The simulation yielded spatially distributed hydraulic parameters: including flow velocity, shear stress and flow depth. Second, we derived a high-resolution erosion map using LiDAR-based change detection. Pre-event (2019) and post-event (2021) 1-m DEMs were differenced to compute elevation changes along the river corridor. Areas exhibiting a depth loss exceeding 0.5 m were classified as “significant erosion” and used as the binary response variable (erosion/no erosion) in subsequent modeling. Finally, we developed a GAM to predict erosion probability as a function of the HEC-RAS-derived hydraulic variables. Our logistic GAM achieved AUC-ROC of 0.8 through non-linear s-terms and physically meaningful te-interactions (shear×depth, velocity×depth). Comparison with field survey results confirmed that the model reliably identifies zone prone to bank erosion. This approach successfully bridges the gap between hydraulic modeling and observed erosion patterns, revealing non-linear, spatially variable relationships that simple thresholds miss. The proposed methodology provides a robust, data-driven framework for translating HEC-RAS outputs into high-resolution erosion risk maps. Future research should integrate spatially explicit sediment characteristics to quantifiy the local mobilisation potential and test the model across a range of geomorphological and lithological settings to further improve its transferability and predictive accuracy.
This research forms part of the MABEIS III project ("Mass Movement Information System for Rhineland-Palatinate"), funded by the Rhineland-Palatinate´s State Office for Mobility (LBM) and the State Authority for Geology and Mining (LGB).
How to cite: Arnold, A., Hofmann, J. P., Malka, A., Hettwer, F., and Enzmann, F.: Hydraulic hotspots vs. erosion reality - a GAM approach to quantifying bank erosion using HEC-RAS and LiDAR difference images, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20860, https://doi.org/10.5194/egusphere-egu26-20860, 2026.
Semi-enclosed coastal systems such as the Ría de Arousa sustain high biological productivity and host aquaculture activities of major ecological and economic relevance. In this region, mussel farming (Mytilus galloprovincialis) on rafts dominates, making it the most productive area in Europe. The scale of this activity introduces additional pressures on the ecosystem, among which the production of biodeposits and their influence on the benthos are key aspects for the sustainable management of the industry.
From this perspective, Lagrangian particle transport modelling offers a valuable tool for quantifying and anticipating the dispersion and fate of these
biodeposits. In this work, we employ the MOHID-Lagrangian model, extended with new modules specifically designed to represent the behaviour of particles denser than seawater. In particular, we implement a resuspension scheme and propose a parameterisation for biodeposit degradation, thus extending capabilities traditionally applied to neutrally buoyant particles into a fully three-dimensional context.
The aim is to characterise biodeposit dispersal in the vicinity of a mussel raft and evaluate the model’s sensitivity to the newly introduced parameterisations, with the ultimate goal of advancing towards a more realistic and predictive representation of biodeposit fate in intensive aquaculture systems.
How to cite: Riveira Varela, M. and Shabani, M.: Modeling the Transport of Biodeposits in the Vicinity of a Mussel Raft, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10947, https://doi.org/10.5194/egusphere-egu26-10947, 2026.
