Riverbank erosion is a significant contributor to sediment transport in rivers and a key factor shaping river ecosystems, which are affected by natural and human activities. Its dynamics depend on a variety of factors, including river flow, water levels, soil properties and composition, groundwater flow, topography, climate, soil moisture, temperature, and vegetation. The main drivers of riverbank erosion are particle detachment by water flow, gravity-induced mass failure, and seepage erosion. While these processes shape river channels and floodplain morphology and support ecological functions like habitat creation, they also pose risks such as land degradation and infrastructure damage.  In seasonally frozen rivers, bank erosion dynamics are further complicated by unique climatic and hydrogeomorphic conditions, including temperature fluctuations and variations in groundwater flow. These additional processes can cause erosion by themselves and can interact with the other processes. Especially, the interactions between these factors remain poorly understood, hindering accurate predictions of bank erosion events. This study examines how topography, river stage changes, groundwater flow, soil moisture, and temperature variations affect riverbank erosion in seasonally frozen rivers. The research focuses on three objectives: (i) assessing how topography influences riverbank erosion, (ii) examining the role of river stage fluctuations and soil types in erosion processes, and (iii) analyzing the impact of freeze-thaw cycles on groundwater movement and soil stability, bank erosion. A two dimensional (2D) vertical bank erosion model was developed that integrates temperature dynamics with groundwater flow, allowing realistic simulations of temperature-induced changes in soil permeability and groundwater behavior. The framework applied with dynamic boundary conditions, offering novel insights into riverbank erosion mechanisms. The simulations were at this first stage performed by using a hypothetical riverbank geometry. First findings show that the interactions of processes can lead to temporally varying rates of erosion which cannot be understood in isolation. Bank geometry is expected to play a significant role, with some profiles more prone to collapse than others. Additionally, river stage fluctuations and dynamic soil conditions are likely to exacerbate erosion risks. These insights will support the development of predictive tools for sediment management, climate-resilient riverbank protection, and sustainable ecosystem management in cold-region rivers.

Keywords: Riverbank erosion, groundwater modeling, temperature, seasonally frozen rivers, numerical modeling, freeze-thaw cycles.

How to cite: Tedla, H. Z., Lotsari, E., and van Rooijen, E.: Riverbank erosion numerical modeling: groundwater and temperature dynamics in seasonally frozen rivers using a hypothetical bank geometry, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7240, https://doi.org/10.5194/egusphere-egu25-7240, 2025.

The hydrological and sediment transport regimes of Mediterranean river basins are critical for effective water resource management, especially in regions vulnerable to land degradation and erosion. This study investigates the Seman River Basin in Albania, employing the WASA-SED (Water Availability in Semi-Arid environments – SEDiments) model to simulate flow and sediment dynamics. Daily data on precipitation, temperature, soil properties, land use, discharge, and suspended sediment concentrations were used to quantify runoff and sediment yields in the basin. Results demonstrate a strong correlation between rainfall intensity, land surface cover, and sediment transport, with notable seasonal variations in runoff. Sediment deposition within the basin significantly reduces the storage capacity of local dams, aggravating water resource challenges. Additionally, land use changes, particularly deforestation and agricultural expansion, exacerbate sedimentation and impact the hydrological regime. This study provides valuable insights into the sediment dynamics and hydrological processes of Mediterranean river basins, offering a predictive tool for water resource management and sediment mitigation strategies. The findings underscore the need for sustainable land and water management practices in the Balkans and similar environments.

How to cite: Doko, A., Francke, T., and Bronstert, A.: Analyzing Hydrological and Sediment Transport Patterns in the Seman River Basin, Albania, Using the WASA-SED Model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5927, https://doi.org/10.5194/egusphere-egu25-5927, 2025.

Morphological change in rivers is a dynamic and complex phenomenon affected by several environmental conditions and hydraulic processes, which are mainly related to the composition and the susceptibility of erosion of the river channel and watershed. While erosion occurs constantly at low rates most of the time, high flow events such as flash floods can lead to a severe increase in erosion and sedimentation rates, which can have negative effects on transportation infrastructures, residential areas and even the efficiency of hydropower projects. With the future projections of climate change showing an increase in the frequency of such events, a good understanding is important in assessing the impact they will have in already existing and planned riverside uses.

However, investigating sediment rates is a difficult task both in the field and through numerical modelling. Especially in small streams, quick events characterized by extreme flow, can produce a significant portion of the annual sediment load in the matter of a few days or hours. Satellite and drone data or acoustic/optical devices provide scarce observations and pointwise measurements respectively, thus lacking the time and spatial resolution necessary to capture the overall dynamics of the river. The development of 2D and 3D numerical models would also prove as a computationally demanding task when applied to larger scale areas such as a river reach and long simulation periods (i.e., tens of kilometers and decades). Utilizing a well-documented 1D model is a viable option due to the accessibility and low computational demands.

For these reasons, the objective of this study will be establishing a 1D sediment transport model through HEC-RAS, relying on evidences from case studies prone to hydrological quick events. The calibration procedure is deterministic parameter testing, such as sediment transport functions and cohesive factors, with the aim of reconstructing the sediment input and deposition based on the existing bathymetries and measured suspended sediment concentrations during floods.

The expected results would be assessing the sediment quantities during flood events, and the impact on the river morphology in the long term. Running various climate change scenarios, such as SSPs (Shared Socioeconomic Pathways) will provide the uncertainties of river morphology changes in the future, burden with increasing floods frequency,

How to cite: Lleshi, R., Guerrero, M., Conevski, S., Di Federico, V., and Rüther, N.: Large Scale Morphological Changes Due To Flash Floods In Small Streams Under Climate Change Scenarios, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16976, https://doi.org/10.5194/egusphere-egu25-16976, 2025.

Over the past two centuries, river regulation practices in Europe have significantly altered river systems through straightening, channelization and bedload retention. These modifications, coupled with the implementation of transverse structures such as hydropower facilities, have adversely affected riverine ecosystems, floodplains and sediment dynamics. River widening projects aim to address these challenges by creating more space for rivers, thereby improving the health of these natural systems. In Tyrol, Austria, between Stams and Rietz, a restoration project on the Inn River included the removal of most bank protection, the widening of the river up to 75 meters, and the creation of a dead branch and a side channel. On a length of 3 km, this measure re-established aquatic as well as terrestrial habitats. Shortly after completion, a 50-year flood event caused significant changes along the restoration zone, including the breaching of the dead branch, which subsequently connected to the main channel. These morphodynamic changes were documented using two airborne laser bathymetry (ALB) surveys and an echo-sounding survey for cross-sectional profiles.

Morphodynamic models are key tools for understanding sediment transport processes in rivers and providing insights into riverbed dynamics and sediment budgets over time. For this study, the Telemac2D hydrodynamic model, coupled with the Gaia sediment transport module, was employed to simulate the hydrograph of the HQ50 flood event. The model accounted for complex bedload behavior, including lateral slope effects and bank failure, which are essential processes in river restoration. A stable sediment budget with inflow rates equal to outflow rates was assumed due to the uncertainty in bedload inflow rates. A sensitivity analysis was conducted using various transport equations, including Meyer-Peter & Müller, Einstein & Brown, Hunziker, and Wilcock & Crowe. To assess model performance, metrics such as mean change in elevation (MCE), root mean square error (RMSE), and a newly developed erosion and deposition pattern index (EDPI) were analyzed. All transport equations replicated the general survey patterns, with the Meyer-Peter & Müller equation achieving the lowest MCE and RMSE errors and the highest EDPI values. Despite these promising results, unrealistic behavior was observed since none of the transport models accounted for the movement of the coarsest sediment fraction, leading to bed coarsening as fine material was preferentially transported out of the model. Furthermore, the Hunziker and Wilcock & Crowe equations yielded unrealistically low transport rates, resulting in reduced erosion and deposition compared to the Meyer-Peter & Müller and Einstein & Brown equations. These limitations highlight uncertainties in shear stress calculations for alpine rivers characterized by large particle sizes. Further research is recommended to address these issues and enhance the accuracy of sediment transport modeling in similar contexts.

How to cite: Siedersleben, J., Zöschg, H., and Schletterer, M.: Analyzing morphodynamics along a river widening: Applicability of different transport equations in 2D numerical modeling, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16570, https://doi.org/10.5194/egusphere-egu25-16570, 2025.

In river confluences, the two branches may have different water temperatures and sediment loads, which induce strong transverse density gradients. These gradients, in turn, drive the formation of secondary currents, which interact with those generated by channel curvature. Specifically, density gradients can either enhance or counteract curvature-induced secondary flows, and their impacts on flow and sediment transport require proper modelling approaches. Three-dimensional (3D) models naturally account for these dynamics and provide detailed predictions of flow and temperature fields, but cannot be applied to long-term morphodynamic simulations because of prohibitive computational demand. By contrast, traditional two-dimensional (2D) models are computationally more efficient, but do not account for 3D flow structures that are particularly relevant for river confluences. To fill the gap, a 2D depth-integrated hydro-morphodynamic model is enhanced, through appropriate parametrization, to account for the density-driven secondary flows and their effects on the flow field, mixing, sediment redistribution and, ultimately, on the morphodynamic evolution of the riverbed.

The enhanced 2D model is applied to the Yangtze River-Poyang Lake confluence, where field measurements have shown that temperature-induced density gradients play a critical role in shaping flow patterns, secondary currents, and the riverbed evolution. Interestingly, these effects vary throughout the year due to seasonal differences in temperature and discharge between the two branches of the confluence. Density-induced secondary currents, which superimpose or modify the curvature-induced helical flows, develop at the confluence apex where the two streams merge. Their inclusion in the 2D modelling framework improves the agreement of numerical results with ADCP field measurements, thus supporting the reliability of the model.

The efficiency of the 2D model, combined with its ability to represent key physical processes through the parametrization of density-driven effects, also allows to perform long-term simulations with mobile bed conditions. These simulations highlight the significant role of secondary flows, driven by both streamline curvature and spanwise density gradients, in sediment transport and bed morphology at the river confluence, confirming that the enhanced 2D model is a valuable tool for long-term morphodynamic studies in large river systems.

How to cite: Lazzarin, T., Xu, L., Yuan, S., Hoitink, T., and Viero, D. P.: Modelling Density-Driven Secondary Flow with a 2-D Depth-Integrated Model: Insights from the Yangtze River-Poyang Lake Confluence, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-820, https://doi.org/10.5194/egusphere-egu25-820, 2025.

This study aims to develop a Lagrangian stochastic model for simulating suspended sediment transport in open channel flows. The model focuses on a pair of particles, describing the trajectories of paired particles, which are dependent on the Reynolds number. It uses relative particle velocity as a foundation for tracking sediment motion, with key factors such as separation distance and relative velocity being critical in defining particle interactions and their role in separation processes. This model captures non-Gaussian turbulence features in Eulerian statistics to construct a relative velocity probability density function. A structure-function approach is employed to derive Eulerian velocity moments from velocity increments, ensuring stable dispersion by considering relevant scale properties. The model incorporates the Langevin equation for relative velocity, consisting a drift term defined by conditional acceleration and a Eulerian probability density function, and a random term defined by a scale-dependent diffusion coefficient influenced by viscous effects, exhibiting Brownian motion properties.

The model extends the fluid particle framework to sediment particles through the principles of force balance and accounts for the resuspension mechanism for sediment particles. In sediment transport, the influence of the resuspension mechanism on the two particles must be considered. This mechanism is different from those in fluid particle models and single-particle sediment models. Additionally, the relative velocity model is transformed into an absolute velocity model, and two-particle coefficients are introduced to determine particle motion. The Ornstein-Uhlenbeck (OU) process is employed to simulate velocity fluctuations for individual particles.

Compared to single-particle models, this two-particle stochastic model investigates turbulent sediment transport in terms of relative velocity and separation distance variations. We analyze the variation of the diffusion coefficient across scales by tuning specific parameters. Results are compared with direct numerical simulation (DNS) data across different Reynolds numbers to calibrate the model coefficients effectively. The initial findings provide valuable insights into the influence of turbulence characteristics on sediment behavior, particularly in relation to relative velocity and separation distance variations. This work contributes to a deeper understanding of the complex interactions governing sediment transport in turbulent open channel flows.

How to cite: Chen, H. Q. and Tsai, C.: Two-Particle Stochastic Model for Suspended Sediment Transport Using Spatial Relationship with Particles, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15745, https://doi.org/10.5194/egusphere-egu25-15745, 2025.

Sediment transport problems in rivers often arise under conditions involving a dynamic and complex free surface. Local scour around hydraulic structures can pose significant threats to the stability and safety of riverine infrastructure during extreme discharge events. To date, computational fluid dynamics (CFD) software using the two-phase approach are used for such scenarios, which comes at the cost of significant computational resources. This contribution presents a non-hydrostatic Navier-Stokes equations solver on a σ-coordinate grid that allows the grid to follow the variations of the free surface as well as the bottom. The approach is significantly more efficient then said CFD models. The model is developed within the open-source hydrodynamics framework REEF3D, which allows for use of the parallelization and high-order finite difference frameworks. For discretization, it uses a Godunov-type scheme for shock-capturing properties, allowing for stable and accurate representation of complex free surface conditions, such as hydraulic jumps. Bed load and suspended load transport formulations are implemented based on standard formulations. The possible sediment transport and scouring effects around the large bridge piers of a relatively old bridge over the river Nidelva in Trondheim, Norway are investigated. Due to the contraction effects of the piers, subcritical flow is forced for certain conditions. The numerical model captures the hydrodynamics and the free surface realistically, showing the possibility for a more efficient alternative to two-phase flow CFD simulations in such scenarios.

How to cite: Bihs, H. and Wang, W. W.: Non-Hydrostatic and Shock-Capturing Modeling of Free Surface Flow Driven Sediment Transport around Bridge Foundations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20462, https://doi.org/10.5194/egusphere-egu25-20462, 2025.

The diffusive wave or the zero-inertia (ZI) model for surface runoff modeling is derived by neglecting the local and convective acceleration terms from the two-dimensional (2D) depth-averaged shallow water equations (SWE). The ZI model is computationally efficient and highly accurate compared to the SW models for modeling low subcritical (Froude number < 0.5) flood propagation problems. The current study presents a Finite Volume (FV) method-based ZI flow model – zeroInertiaFlowFOAM, developed using the OpenFOAM^® framework [1]. The model utilizes the implicit time discretization scheme and the Picard iteration scheme for the linearization of the non-linear momentum equation. The stabilized and adaptive time-stepping algorithm implemented in the present model adjusts the future time step size based on the convergence characteristics of the iterative scheme at the present time step, thereby enhancing the computational efficiency. The existing ZI model – surfaceFlowFOAM [2] suffered from high mass balance errors (MBE) and chequerboard oscillations while simulating flood flows due to high rainfall intensities over surfaces with steep bed-slopes. The present model is a modified version of surfaceFlowFOAM. In the present model, the velocity is calculated from the momentum equation at the element centroids of the collocated grid-system. The calculated velocity is used to solve the continuity equation, where the divergence of the flux term is discretized using the upwind scheme. This relates the gradient of the flow depth (∇h) to the values at the consecutive element centroids, thereby eliminating the possibility of chequerboard instability arising in the regions where the water-surface slope changes sharply. It significantly reduces the restrictions on mesh generation for such problems, thereby increasing the computational efficiency when compared to surfaceFlowFOAM. Moreover, the modified discretization technique adopted in zeroInertiaFlowFOAM has helped in achieving high mass balance accuracy which was another significant limitation in surfaceFlowFOAM. The applicability of zeroInertiaFlowFOAM has also been verified and validated against the standard benchmark problems from the literature.

References

[1] Jasak, H., A. Jemcov, Z. Tukovic. (2007). OpenFOAM: A C++ library for complex physics simulations. In Vol. 1000 of Proc., Int. Workshop on Coupled Methods in Numerical Dynamics,1–20. Dubrovnik, Croatia: Inter-University Center

[2] Dey, S., Dhar, A. (2024). Applicability of Zero-Inertia Approximation for Overland Flow Using a Generalized Mass-Conservative Implicit Finite Volume Framework. Journal of Hydrologic Engineering, 29(1), 04023042.

How to cite: Dey, S.: zeroInertiaFlowFOAM – a OpenFOAM®-based computationally efficient, mass-conservative, implicit zero-inertia flow model for flood inundation problems on collocated grid-systems. , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17402, https://doi.org/10.5194/egusphere-egu25-17402, 2025.

Braided rivers are the most dynamic type of rivers, with a rapid and intricate morphological evolution. A limited understanding and inadequate algorithm implementation of specific morphological processes limits the prediction capabilities of physics-based models. The design of structures, infrastructure, and other interventions is consequently hampered. In recent years artificial intelligence (AI) techniques rapidly gained popularity across different contexts. Additionally, the availability of satellite images increased. This research sets a novel attempt to predict the planform evolution of braided rivers by means of deep learning and satellite images. The Brahmaputra-Jamuna River, in India and Bangladesh, was selected as case study. A convolutional neural network (CNN) with U-Net architecture was developed. The model was trained with the Global Surface Water Dataset (GSWD). The goal of the model was to classify each pixel as either "Non-water" or "Water". Four images, representative of the same month over four consecutive years, were used as input. The fifth-year image represented the target. The model demonstrated good skills in predicting the planform development. Processes like the migration of meanders, the abandonment of channels, and the evolution of confluences and bifurcations were often well captured. However, a lack of temporal patterns was noticed. More complex phenomena, like the formation and shifting of channels, were never predicted. The total areas of erosion and deposition were constantly underpredicted. Metrics such as precision, recall, F1-score, and critical success index (CSI) were tracked. Overall, our model achieved a 5-6% total improvement of these metrics compared to the benchmark method for which no morphological change is assumed to occur. Our model could be useful as a preliminary tool for water management authorities in India and Bangladesh. It can support the prioritisation of bank protection measures in areas subject to erosion or land reclamation projects in areas subject to deposition and assist inland navigation. Given the inherent tendency of the model to underpredict erosion, caution is always advised. More research is required to improve the current model. Despite this, deep-learning modelling could become a potentially valuable field of research. Testing alternative model architectures, increasing the datasets size, and incorporating additional data, such as water levels or river discharge, are some of the proposed strategies to improve the model performance.

How to cite: Magherini, A., Mosselman, E., Chavarrías, V., and Taormina, R.: Deep learning for planform predictions of braided rivers, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-650, https://doi.org/10.5194/egusphere-egu25-650, 2025.

Deriving sediment yield (SY) from discharge (Q) and suspended sediment concentration (SSC) measurements is subject to multiple sources of error, including the sampling method, the sampling scheme and frequency, the load calculation method, and the measuring period. While the uncertainty from these individual sources of error has been studied in various contexts, their combined effect on SY calculations remains largely unquantified. This is mainly due to their complex and counteracting influences, the absence of detailed sampling protocol information, and the lack of true reference data. Still, estimating the total uncertainty on current and historical SY measurements is crucial to understand how these observational errors propagate in SY modelling and can impact subsequent model interpretation and decision-making.

Here, we aim to develop a tool that can provide realistic ranges of total uncertainty in SY observations worldwide for which limited metadata is reported. We do this by means of Monte Carlo simulations and machine learning. Using available long-term daily Q and SSC series, we quantify the effect of measurement-related sources of error, as well as their relative importance, on SY calculations. We apply this method on a (spatially) diverse selection of ∼180 gauging stations and further explore the relationship between SY uncertainty and catchment characteristics, including upstream area, land cover, and climate. Preliminary findings indicate that the range of uncertainty in SY calculations is mainly influenced by the sampling frequency, whereas the load calculation method and the sampling scheme can introduce important biases. Measuring errors on individual Q and SSC observations have relatively little impact on total SY uncertainty, provided that these measurements are unbiased. When considering long-term average SY, the length of the measuring period then becomes the most important source of uncertainty. Overall, the combined effect of these sources of error can lead to deviations up to three orders of magnitude from the true SY. Using these sampling-related variables and catchment characteristics derived from global hydro-environmental datasets, we further apply a gradient boosting algorithm to predict total uncertainty in annual SY and achieve a Nash-Sutcliffe model efficiency of ∼0.76. The model resulting from this work can thus provide scientists with realistic uncertainty estimates on existing SY observations with only basic metadata information available.

How to cite: Tan, F., Borrelli, P., de Oliveira Fagundes, H., and Vanmaercke, M.: How good are sediment measurements? An integrated approach to quantifying total uncertainty in metadata-limited annual suspended sediment yield observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9845, https://doi.org/10.5194/egusphere-egu25-9845, 2025.

A hydropeak is a rapid increase in river discharge induced by a hydroelectric dam when optimizing energy production.  These flow fluctuations occur in many regulated rivers and can influence sediment transport and fluvial habitat. The present study investigates the relative importance of hydropeaks versus natural floods for bedload sediment transport in the Ésera River, Central Pyrenees, Spain. An acoustic Doppler current profiler (ADCP) was used to measure both stationary time series and spatial distributions of apparent bedload velocity, which is the bias induced in ADCP bottom track velocity (Doppler sonar) due to bedload transport. A Sontek RiverSurveyor M9® ADCP, coupled with a Leica GS15® Real-Time Global Navigation Satellite System (RTK-GNNS), was deployed on a tethered floating survey platform from the road bridge at the Santaliestra monitoring section, which is approximately 13 km downstream from the hydropower plant.

During two measurement campaigns in 2019 and 2020, a total of 29 of the stationary ADCP apparent bedload velocity measurements distributed across the channel section were coupled with synchronous adjacent physical bedload samples collected with a Helley-Smith sampler.  Correlation of such paired samples can be used to develop a calibration relation between observed ADCP apparent bedload velocity (m/s) and bedload sediment transport rate (kg/m/s). The physical bedload samples were processed in the laboratory to obtain fractional bedload transport rates. The paired data set was insufficient to develop a strong overall calibration relation, but fractional results aligned with calibration relations developed in other rivers with similar mixed sand/gravel bed materials.

A total of 13 spatial surveys of apparent bedload velocity were obtained for different flow rates, during both hydropeaking events and natural floods. Initial observations suggest natural floods result in greater sediment transport in the Santaliestra section due to the input of sediment from tributaries. Nonethless, hydropeaks were observed to partially destabilize/mobilize the bed, and thus contribute to sediment transport and morphodynamic processes.

How to cite: Rennie, C. D., Ville, F., Vericat, D., and Batalla, R. J.: ADCP measurements of bedload due to hydropeaking versus natural floods, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20662, https://doi.org/10.5194/egusphere-egu25-20662, 2025.

Accurately predicting, modelling and measuring bedload transport rate remains a challenge even after a century of research and various approaches. Traditionally measurements of bedload transport rate in field setting have been done with labor-intensive and difficult to use mechanical equipment such as bedload samplers or traps. Mechanical devices are often intrusive, meaning that the devices’ presence can influence the shape of riverbed and the measured bedload transport rate during the measurement. These devices are also limited in their capability to capture the spatial and temporal fluctuations of bedload transport and only describe dimensionless mean transport rate from a point or a section. Image processing techniques such as particle image velocimetry and optical flow combined with background subtraction and image labeling methods enable continuous, non-intrusive two-dimensional bedload velocity and bedload transport rate measurements over large areas. These image processing techniques have been previously successfully applied in lab conditions to measure bedload transport rates from video data sets but not in field conditions.

The focus of this study is 1) to apply image processing techniques to underwater video data sets to measure seasonal bedload transport rates in various sediment transport conditions and 2) to understand and compare the seasonal variation in bedload transport measured with image processing techniques and traditional mechanical measurements.

To cover various sediment transport conditions, the study is based on field data collected over various years (2021-2024), seasons (winter, spring, autumn), and flow conditions (open channel and ice-covered) at sub-arctic Pulmanki river, which is in northern Finland (~70°N latitude) and drains to the Arctic Sea. The novel results are presented and show that the method is promising in enhancing the understanding of sediment transport processes and the seasonal transported amounts in sub-arctic river conditions.

How to cite: Välimäki, J.-M., Lotsari, E., Eltner, A., and Takala, T.: Measuring seasonal bedload transport rates in a sub-arctic river using image processing techniques, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18955, https://doi.org/10.5194/egusphere-egu25-18955, 2025.

Suspended sediment plays a crucial role in shaping stream morphology and maintaining ecological balance, yet the main controls on its sources and dynamics in forested mountain catchments are still poorly documented. In this study we aimed at assessing suspended sediment spatio-temporal sources and transport dynamics in a Mediterranean mountain catchment. A relevant role might be played by large wood debris in suspended sediment retention and release: large wood structures can significantly influence sediment dynamics by trapping sediments and creating stable habitats for aquatic organisms. This aspect is particularly relevant in forested mountain streams where wood accumulation can alter flow patterns and sediment transport mechanisms.

The experimental activities were carried out in the densely forested Re della Pietra catchment located in Tuscany, Central Italy.

To assess suspended sediment spatio-temporal dynamics, field measurements were conducted since December 2024, including monitoring of turbidity at the catchment outlet using a high-definition turbidimeter, stream stage measurements, soil moisture measurements at two depths, and the main meteorological variables.

Preliminary results show a significant correlation between turbidity, rainfall intensity and stage variation, suggesting that rainfall intensity is crucial in suspended sediment release and transport patterns. Notably, pronounced turbidity peaks were observed during moderate to intense storm events occurred during the wet season but did not correlated to meteorological variables. The analysis of the hysteresis loops between turbidity and stream stage (as a proxy of discharge) reported that the 15% of the loops were clockwise, suggesting that suspended sediment primarily originates from local sources, mostly during the wet season.

The study highlights the relationships between suspended sediment transport, large wood debris, and hydrological variables, emphasizing the need for further investigation of the factors affecting suspended sediment transport in forested mountain environments. The determination of flow rating curve is in progress, and future analysis will consider suspended sediment concentration and discharge data. The large wood impact will be studied through the visual analysis of the photographic documentation produced by cameras located at the catchment outlet.

How to cite: Chirici, D., Murgia, I., Verdone, M., Innocenti, L., Nigro, M., Manca, F., Dani, A., Preti, F., Belli, G., Gheri, D., Mao, L., Marchetti, E., Solari, L., and Penna, D.: Investigating Suspended Sediment And Large Wood Dynamics in a Mountain Forested Catchment, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19543, https://doi.org/10.5194/egusphere-egu25-19543, 2025.

Physical models are valuable tools for investigating changes in river morphology while also allowing the analysis of three-dimensional processes such as scour in bends or the vicinity of hydraulic structures. An important aspect is an accurate assessment of the river bed and morphological structures that occur, which today is often based on optical measurement systems, such as LiDAR, or photogrammetric techniques like Structure for Motion (SfM). These sensors are usually mounted on tripods, requiring multiple look angles to cover the whole model, and therefore need to be manually repositioned several times. Alternatively, they can be mounted on overhead tracks, limiting the possible look angles and requiring expansive installation.

To overcome these limitations, this study utilized a drone equipped with a high-resolution camera to survey morphological bed changes of a 70 m long and up to 6 m wide physical model with a movable bed and fixed rip-rap embankments. The bed material consisted of coarse sand and fine gravel with a mean diameter of 2.1 mm. Several surveys covering a total area of 180 m² were carried out and drone-based SfM results were compared with data obtained using a terrestrial laser scanner (Leica RTC360). The DJI Mavic Mini 3 Pro drone was equipped with a 48 MP camera, featuring a 1/1.3'' CMOS sensor which captured up to 240 camera positions from three vertical angles within 30 minutes. This was a similar acquisition time required by the tripod-mounted laser scanner to cover the whole model with six setups. Post-processing, from ground control point detection and tie point matching to cloud construction and digital elevation model (DEM) generation, was automated in this study to reduce processing time.

By comparing the DEMs produced by SfM and the RTC360, it became obvious that SfM cannot only map morphological structures but also produces denser point clouds, with a mean surface point density of 127 pts/cm² compared to 75 pts/cm² by the laser scan. The mean absolute cloud-to-cloud distance for the model bed is 1.8 mm, with a standard deviation of 1.5 mm. This compares favorably to the accuracy of the RTC360 of 1.9 mm at a distance of 10 meters.

Notably, there are disagreements between the SfM model and the laser scan, especially in areas with coarser materials, e.g. rip-rap at the embankments, or areas with low-feature texture, e.g. plastic structures or smooth concrete faces. The final calculated volume differences from the resulting DEMs before and after an experimental trial also show good agreement, with a 3 % discrepancy in the volume difference.

The results of this study showed that the accuracy of drone-based SfM-generated DEMs is similar to that of an RTC360 with much lower equipment costs. Furthermore, the mobility of drones offers the advantage of achieving a wider range of look angles, which improves the quality of the resulting SfM model. Hence, the application of drone-based SfM for morphological measurements in laboratory experiments is a promising technique for a wide range of measurements of morphological processes.

How to cite: Pirker, M., Haun, S., and Schneider, J.: Evaluating drone-based photogrammetry for morphologic mapping of a hydraulic model with a mobile bed, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20898, https://doi.org/10.5194/egusphere-egu25-20898, 2025.

Drawdown flushing in reservoirs is a key scheme for reservoirs water and sediment regulation in Yellow River basin, making it possible to maintain the effective storage capacity of the reservoirs. In early September of 2023 and 2024, joint operation of key reservoirs in the upper and middle reaches of the Yellow River was carried out to implement sediment discharge. In 2023, the water and sediment regulation resulted in an outflow of 610 million m³ from Liujiaxia Reservoir. Four reservoirs, including Qingtongxia, Haibowan, Wanjiazhai, and Longkou, discharged a total of 75 million tons of sediment, consuming 8 m³ of water per ton of sediment. In 2024, the water and sediment regulation resulted in a water output of 1.09 billion m³ from Liujiaxia Reservoir. The five reservoirs of Shapotou, Qingtongxia, Haibowan, Wanjiazhai, and Longkou Reservoirs discharged a total of 144 million tons of sediment, consuming 7.5 m³ of water per ton of sediment. Through the practice of water and sediment regulation, it has been proven that flushing is a systematic response of reservoir deposition to the drawdown of water level. The flushing process is unsteady, and the sediment concentration at the outlet increases rapidly at first and then decreases rapidly. The scouring amount is positively correlated with the magnitude of inflow discharge and duration of drawdown. The larger the discharge, the longer the duration, and the more sediment discharge. 

How to cite: Yang, F., Yan, X., and Wang, Q.: Water and sediment regulation in past two years at upper and middle Yellow River, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14657, https://doi.org/10.5194/egusphere-egu25-14657, 2025.

Abstract: Under the combined operation of upstream cascade reservoirs with the Three Gorges Project as the core and the comprehensive impact of climate change, the water and sediment conditions in the middle and lower reaches of the Yangtze River have undergone significant changes, which have had a profound impact on the evolution and pattern of river-lake system. This paper takes the confluence reach of the Yangtze River Mainstream and Dongting Lake as the research object. Through the physical model(plane scale 1:400, vertical scale 1:100) experiments, the confluence process of flow and sediment and the evolution rule of erosion and deposition of the Yangtze River Mainstream and Dongting Lake outlet channel under different silt-discharge and river lake boundary conditions were explored, and the influence mechanism of different erosion and deposition conditions on the river-lake relationship was analyzed. The results indicate that considering the further scouring development of the main stream of the Yangtze River in the future, under the condition of controlling the water level at the model outlet (Luoshan station) to drop by 3m, the longitudinal gradient of the water surface in the confluence channel of Dongting Lake increased by about 20%, showing a scouring trend, and the emptying effect of the Yangtze River Mainstream on the Dongting Lake was enhanced. In addition, under the condition of controlling the flood flow of 50000m³/s at the outlet, with the increase of the confluence ratio between Dongting Lake and the Yangtze River Mainstream, the scouring intensity in the river and lake confluence area increased, and the elevation difference between the main stream and tributary riverbed increases, resulting in the increasing jacking effect of Dongting Lake outflow on the main stream. The relevant achievements can provide new insights and decision-making references for maintaining the healthy river-lake system pattern and interaction relationship in the middle and lower reaches of the Yangtze River.

Key words: flow and sediment variation; river-lake relations; physical model experiments; Dongting Lake; Middle reaches of the Yangtze River

How to cite: Wang, H., Yao, S., Guo, X., and Guo, C.: Influence mechanism of erosion and deposition evolution of Dongting Lake confluence channel on river-lake relationship under new water and sediment conditions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12100, https://doi.org/10.5194/egusphere-egu25-12100, 2025.