Accurate estimation of sediment size and substrate classes in fluvial remote sensing is pivotal for habitat modeling and hydrodynamic applications. While recent advancements have adopted computer vision based approaches (i.e. deep learning), the complexity of setting up these algorithms, along with the requirement of dedicated hardware, and the lack of readily available tools, hinder their wider adoption. This study presents a novel, user-friendly two-step tool tailored for precise substrate class estimation in clear-water river environments from ultra high-resolution orthoimagery, typically coming from UAVs. Leveraging image texture properties (evaluated with the co-occurrence matrix), image color channels (typically Red, Blue, and Green bands) and machine learning classificators (i.e. Random Forest, Support Vector Machine), the proposed methodology is able to accurately identify substrate classes ranging from fine sediments (e.g. sand and lime), various size gravel and cobbles, and boulders, both submerged (wet) and above water. It is a 2-step methodology that involves (a) manual labeling of homogeneous substrate class patches within any Geographic Information System (GIS) platform, followed by (b) streamlined data input. Validation across three reaches of gravel-bed rivers —Aurino, Piave, and Brenta rivers in NE Italy— with differing sizes and morphologies, and substrate ranging from fine sediments to boulders, yielded F1 scores of 0.86, 0.97, and 0.938, respectively. Some challenges still arise when classifying substrate in areas where visibility and light conditions are significantly altered, such as in very deep water, within tree canopy shadows, or due to strong sun reflections. Finally, this tool enables easy and accurate substrate class estimations in riverine environments, offering a significant contribution to fluvial studies and applications.

How to cite: Soto Parra, T., Farò, D., and Zolezzi, G.: A robust, user-friendly tool for accurate fluvial grain-size/substrate class estimation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18252, https://doi.org/10.5194/egusphere-egu24-18252, 2024.

Cross-channel variability in bedload transport is a predominant phenomenon in gravel-bed rivers, and is attributed to various aspects, including flow conditions, variations in grain-size distribution, boundary shear stress and channel morphology. These variations need to be considered during direct bedload measurements such that the entirety of collected samples is representative of the transport pattern. As a result, the measurement strategies developed and implemented over decades involve sampling at several positions at a cross-section. The distribution of the sampling points across the channel in large rivers has been implemented in various ways: 1) A given number of sampling points distributed at equal intervals along the channel cross-section; 2) One sampling point located on each transport lane; 3) A-priori approaches which allow for evaluations based on the degree of cross-channel variability of bedload transport.

The first approach is still prone to uncertainties to some degree, since it is still unknown whether transport rates in between two sampling locations can produce significant difference in bedload estimations. The second approach is limited to cross-sections where transport patterns are well known and probably not prone to changes. In addition, it would still be uncertain whether any further variations on the transport lanes may be present. Despite considering cross-channel variability, the third method is difficult to implement when bedload is conveyed through a very small section of the river width, since in such case, the method can lead to overly-numerous sampling points that can be relatively difficult to implement in a measurement campaign.

ADCP Bottom Tracking (BT) is an indirect bedload measurement method that utilizes acoustics to detect movement of bed material. At a given point in time, ADCP sensors record properties of acoustic signals emitted and reflected off the mobile bed.  Bedload transport rates are derived from the BT signal using various approaches described by (Conevski, Winterscheid, Ruther, Guerrero, & Rennie, 2018). The continuous recording of an entire cross-section allows the identification of significant variations in transport and hence the derivation of transport lanes and the effective bedload transport width. This method is still under research but its capability to acquire continuous measurements in high-resolution can be harnessed and used to optimize direct sampling.

The current research proposes to complement direct bedload measurements using ADCP-BT measurements, such that the measurements obtained using the latter approach will be utilized in-situ in a-priori assessment of cross-channel variations in transport. The assessment can then be used to adapt the direct sampling strategy. An approach to auto-detect the “appropriate” sampling locations will be developed with the aim to optimally allocate only few sampling points while retaining the original shape of the bedload curve from ADCP-BT measurements. This approach has the potential to reduce uncertainties in the measurements and also provide the possibility of only sampling at sections that are relevant for bedload calculations and thus providing a time-efficient measurement strategy.

How to cite: Onjira, P., Hillebrand, G., Winterscheid, A., and Reich, J.: Optimization of direct bedload measurements using ADCP Bottom Tracking, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19462, https://doi.org/10.5194/egusphere-egu24-19462, 2024.

The bedload transport rate is the quantified amount of sediment being transported in the active layer of the riverbed. Traditional measuring methods involving laborious mechanical equipment are unable to capture the spatial and temporal fluctuations of bedload transport rate and measurements done with these methods have large uncertainties caused by the disturbance of the hydraulic conditions of the riverbed by the equipment itself. Computer vision-based particle image velocimetry methods have been previously successfully applied to quantify bedload transport rates from video data sets in laboratory conditions, but not in ice-covered and open channel field conditions.

The aims of this study are to 1) to apply image velocimetry methods to underwater video data sets to quantify seasonal bedload transport rates in different types of flow conditions and 2) understand the seasonal variation in bedload transport amounts based on both mechanical and image velocimetry methods.

The study is based on field data, measured at sub-arctic Pulmanki river, located in northern Finland (~70°N latitude) and draining towards the Arctic Sea. The data has been gathered over 2021-2023 during winter (ice-covered, low flow), spring (open channel, high flow), and autumn (open channel, low flow) seasons to cover different possible sediment transport conditions. The preliminary results are presented. They 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.: Quantifying seasonal bedload transport rates in a sub-arctic river using image velocimetry methods, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9321, https://doi.org/10.5194/egusphere-egu24-9321, 2024.

Climate warming is projected to impact hydrology and change ice-cover periods within river channels in polar and permafrost regions. These changes will impact the duration of freezing, frozen, thawing and unfrozen periods, and will affect sediment transport fluxes, notably through riverbank erosion. However, at present, it is difficult to quantify the long-term combined impacts of soil moisture dynamics, changing ambient air, water and ground temperatures and the subsequent rates of thawing and freezing on the fluvial bank erosion processes.

Herein we present a series of 130 laboratory experiments conducted in a novel cryolab morphology facility using a small-scale Friedkin channel. These cryolab flume experiments aim to assess the influence of flow velocity, soil moisture content and temperature of the sediment on riverbank stability with varying ambient air and water temperatures and flow discharges. The riverbank characteristics in the experiments, including sediment grain size, soil moisture and soil temperature, are based on observations from the sub-artic River Pulmankijoki (Finland) during different seasons. The sediment bank blocks (2 cm high) were prepared for each experiment the day before and kept in the cryolab facility overnight to match ambient air temperatures. The topography was measured before and after each experiment, using an array of images collected via a semi-automatic Canon camera. Surface models were produced with structure from motion and volumetric changes were calculated. GoPro cameras filmed videos of bank evolution to determine higher temporal records of bank edge retreat through the experiments. Buoyant sequins were seeded at the start and end of each experiment in order to calculate the surface flow velocities using a particle tracking velocimetry method. A FLIR A655 infrared thermal camera was used to aid understanding the thermal transfers between the flow and the bank.

Results show that the water level had more impact on bank erosion than flow velocities, as at low discharges the full bank height of the channel was less exposed to flow shear. Most critically, the volumetric erosion rate was found to have a non-linear correlation with the air temperature, being highest with an air temperature of 7.0°C (water temperature 7.2°C) and second highest with an air temperature of -2.1°C (water temperature 3.2°C). Conversely the lowest erosion rates occurred at an ambient temperature of -15°C. Erosion occurred as chucks at +1.7 – +3.2°C water temperatures, if the moisture content was high enough, i.e. 18.9% or more, for the sediment block to be frozen. High moisture contents also slowed the heating effect of the flowing water, which propagated through the bank at a lower rate. With the lower soil moisture conditions of 1.1–10.0%, there was not sufficient water within the block to allow it to freeze as a unit. Under such conditions the block acts as loose sediment, and as a consequence water and ambient temperatures have less influence on the erosion rate. These findings have a suite of implications for morphodynamic responses of river channels across defrosting landscapes, which will alter hydrology and sediment fluxes in highly sensitive environments as climate warms into the future.

How to cite: Lotsari, E., de Vet, M., Murphy, B., McLelland, S., and Parsons, D.: Defrosting river banks: morphodynamics and sediment flux, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10175, https://doi.org/10.5194/egusphere-egu24-10175, 2024.

Understanding bedload dynamics is critical for insights into erosion, sedimentation, and channel evolution of river systems. Designing hydraulic structures and validating existing sediment transport models need accurate bedload data. Bedload measurement is done using direct methods involving physical samplers or indirect devices with various acoustic sensors. One widely used indirect method is the impact plate system, which houses an acoustic sensor under it to detect bedload particles. Impact plate systems have been tested under varying velocity, bed roughness and bedload grain sizes. However, the influence of bedload particle shape on the signal characteristics in impact plate systems has yet to be investigated in detail. In the present study, an impact plate system with a hybrid sensor (accelerometer and geophone) attached to the plate's underside is used to understand the role of the shape of the bedload in an experimental flume. Five different particle sizes (4 to 40 mm) are grouped into three classes based on their sphericity index (0.45-0.6, 0.6-0.75, and 0.75-0.9), creating a total of fifteen classes. Ten bedload particles from each class are manually released over the impact plate for 20 runs, and the signals are recorded. It is found that the bedload shape significantly affects the signal characteristics, and with increasing sphericity, the mean maximum amplitude of the signal increases while the centroid frequency decreases. A calibration equation is thus developed between the signal parameters and the sphericity of the bedload grains.

How to cite: Sahu, B. K. and Mohapatra, P. K.: Effect of bedload shape on the signal characteristics of a hybrid impact plate , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-840, https://doi.org/10.5194/egusphere-egu24-840, 2024.

Bedload transport is leading to erosion and deposition processes that shape the rivers morphology. Detecting areas of active bedload transport in rivers is essential for understanding morphodynamic processes within river systems. Previous research has employed various methods to determine sediment transport both in field and in laboratory settings. Field measurements are often limited due to difficult and non-predictable boundary conditions. Laboratory experiments provide opportunities to study sediment transport in a controlled environment with reproducible boundary conditions. However, it remains challenging to non-intrusively detect bedload transport areas across different temporal and spatial scales. In this context, we explore the efficacy of an image processing method to detect bedload transport areas within physical models through the water surface.

The measurements were carried out in a flume with mobile bed, approximately 30 m long and 3.6 m wide, with a longitudinal slope of 0.003. The mobile bed and the feed material consist of the same grain size distribution and represent a well-graded gravel bed river (D_m = 1.50 mm and D₉₀ = 3.06 mm). The simulated hydrographs varied between a HQ₂ flood (Q = 36.4 l/s) and a HQ₅ flood (Q = 49.4 l/s). The discharge was kept constant during the measurement period (approximately 10 minutes). Three cameras were mounted approximately 3 m above the flume covering and area of approximately 18 m x 3.6 m.

The three cameras continuously recorded pictures of the physical model at different temporal resolutions (0.033 Hz – 1 Hz) with a spatial resolution of 1 px/mm². By subtracting the intensity values of consecutive images, spatial values indicating sediment transport intensity could be obtained. The comparison between bedload transport areas identified from image processing and those discerned through visual observation reveals a strong alignment, suggesting the potential of image processing to reflect in-stream bedload transport areas accurately.

Through a combination of image processing methods, visual discrimination, and measurements in the physical model, two threshold values can be depicted. Values in subtracted images exceeding the lower threshold value indicate the initial signs of sediment transport, while values surpassing the larger threshold, signify full sediment transport.

The chosen time interval of image recording requires careful consideration, because it significantly influences the resulting threshold values. A prolonged time (30 seconds) interval with the analysis of many images facilitates the determination of average sediment transport over time, while shorter intervals (1 second), provide a snapshot insight into the distribution of bedload transport areas.

The results of this study reveal the potential of using image processing techniques in laboratory experiments to identify bedload transport areas. With further calibration, these methods hold promise for measuring bedload transport quantity and other more intricate parameters at different temporal and spatial scales.

How to cite: Yu, B., Demuth, P., Weitbrecht, V., and Chen, L.: Determination of spatial-temporal distribution of bedload transport areas in physical model , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2084, https://doi.org/10.5194/egusphere-egu24-2084, 2024.

Structure-from-Motion (SfM) photogrammetry has become an efficient approach in acquiring high-resolution three-dimensional topographic data in geosciences and can be used for measuring submerged riverbed surfaces in shallow and clear water systems. However, the performance of through-water SfM photogrammetry has not been fully evaluated for gravel-bed surfaces, which limits its application to the morphodynamics of gravel-bed rivers in both field investigations and flume experiments. The measurement quality includes: (i) accuracy and precision of the measured underwater bed surface elevations; and (ii) statistical properties (first four moments and structural functions) of the bed surface elevation distributions.

In order to evaluate the influence of bed texture, flow rate, ground control point (GCP) layout, and refraction correction (RC) on the measurement quality of through-water SfM photogrammetry, we conducted a series of experiments in a 70 m-long and 7 m-wide flume with a straight artificial channel under strictly controlled conditions. The channel size was comparable to a small natural stream so that the results could provide insights for not only flume experiments but also for UAV-based field investigations. Bed surfaces with strongly contrasting textures (fine sand cover vs. gravel cover) in two 4 m-long reaches were measured under five constant flows with three GCP layouts, including both dry and underwater GCPs. All the submerged surface models were compared with the corresponding dry bed surfaces to quantify their errors in elevations, moments, and outcomes of structural functions.

The results illustrated that the poorly sorted gravel-bed led to smaller elevation errors than the bed covered by fine sand. The use of underwater GCPs made significant improvements to the elevation accuracy of direct through-water SfM photogrammetry, but counteracted with RC. The elevation errors of the submerged models linearly increased with water depth for all the tested conditions of bed textures, GCP layouts, and discharges in the uncorrected models, but the increasing slopes varied with bed texture. Fine sediment transport caused significant elevation errors, while the static sand dunes and grain clusters did not lead to noticeable errors in the corrected models with dry GCPs. The movement of fine sediment at high flows also led to significant errors in the second to fourth moments, horizontal correlation scales, Hurst exponents, and the errors in statistical properties for both uncorrected and corrected submerged models. The results show that through-water SfM photogrammetry is promising in capturing the topographic and statistical properties of underwater gravel-bed surfaces if fine sediment transport is carefully addressed.

Keywords: Topographic measurement; Structure-from-Motion (SfM); through-water photogrammetry; gravel-bed river; refraction correction

How to cite: Zhang, C., Li, W., Hassan, M., Sun, A., and Qin, C.: Performance of Through-Water Structure-from-Motion Photogrammetry in Gravel-Bed Rivers: An Experimental Investigation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5588, https://doi.org/10.5194/egusphere-egu24-5588, 2024.

Experimental studies were conducted to analyze the alterations in flow behavior and turbulent characteristics over dune-shaped bed features in the absence and presence of downward seepage. Experiments were designed in two categories to understand the flow characteristics: (1) over fixed (immobile) dunes, and (2) dunes made of sand (mobile). In both the categories of experiments, measurements were taken for no seepage condition and the results were then compared when downward seepage discharge of 10% and 15% of the no seepage discharge were allowed through the porous sand bed placed on the flume bed. Instantaneous velocities were collected using Acoustic Doppler velocimeter (ADV) for no seepage and seepage conditions. Significant enhancement in streamwise velocities, RSS, turbulent intensities, turbulent kinetic energy (TKE) values, and bed shear stress was observed at the initial sections on the stoss side and the lee side sections under the influence of downward seepage over both fixed bed as well as mobile bed conditions. The Anisotropic Invariant Map (AIM) illustrates the prevailing 1D anisotropy in the initial and lee side sections of the dune under downward seepage condition. Quadrant and octant analyses show increase in sweep and ejection events in the near bed zone of the initial and lee side section of the dune under downward seepage conditions. Similar patterns of turbulent parameters were observed for the dunes under mobile conditions. However, at the middle sections and crest portion of the fixed bed dune, the magnitudes of turbulent parameters have been found decreasing along the depth of flow. Contradicting the flow and turbulence patterns observed at the crest portion of the fixed dune, the magnitudes of turbulent parameters increase significantly under seepage conditions in the near-bed region of the crest portion. The increase in the magnitudes in the near-bed region of the crest portion for the mobile bed experiments is due to an increase in the scour depth on the lee side section of the dune, owing to higher amount of sediment movement from lee side section of the dune. The increase in scour depth on the lee side section of the mobile dune under the influence of seepage generates higher magnitude of turbulence eddies, which reach the crest portion, leading to a rise in flow velocity and turbulence parameters in the near bed region at the crest portion of the mobile bed dunes, resulting in increased celerity of the dunes under seepage conditions.

Keywords: Two-dimensional dune; downward seepage; acoustic Doppler velocimeter; turbulence characteristics; anisotropy; bursting events; dune morphology.

How to cite: Behera, P. K., Pandey, A., Deshpande, V., and Kumar, B.: Seepage Induced Morphodynamics of Alluvial Channels: Unraveling Dune Dynamics and Flow Characteristics, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1066, https://doi.org/10.5194/egusphere-egu24-1066, 2024.

Numerical simulations are conducted to evaluate the three-dimensional flow field and the bed shear stress in the vicinity of a multiple-pier bridge located in the Po river (Italy), considering the naturally-deformed bathymetry. The use of Detached Eddy Simulations (DES) allows to explicitly resolve the unsteady motion of the energetically important turbulent eddies, and the Volume of Fluid (VoF) method is used to consider the deformations of the free-surface. Simulations are conducted in different hydrodynamic regimes, including free-surface flow and pressure flow that generates in case of deck overtopping. The objective is to investigate the applicability of the DES approach and the VoF technique for simulating the flow dynamics in a full-scale river reach with irregular geometry and a man-made structure on the riverbed. The complex interplays among the river flow, the deformed bathymetry, and the bridge structure are explicitly accounted for, with a precision that far exceeds the typical level of detail achieved through standard methods used for the simulation of river flows (e.g., two-dimensional depth averaged models).

In the case of free-surface flow, the deformed bathymetry, typical of natural rivers, as well as the non-zero angle of attack and the complex shape of the bridge piers, influence the flow field at the bridge site and the distributions of bed shear stresses. This aspect highlights some limitations that arise when canonical cases (i.e., piers of regular shape and angle of attack of 0° over a flat bed) are considered in place of real complex geometries. The impact of the lateral flow contraction on the flow fields and on the potential of sediment erosion is limited in the present case due to the reduced width of the piers and the large distance between them, resulting in a low blocking ratio.

Transitioning to the pressure-flow regime increases the free surface elevation upstream of the bridge and induces the formation of a high-velocity orifice flow beneath the deck, with regions of high velocity extending far downstream. Recirculation regions are observed below and downstream of the deck. Compared to an equivalent free-surface case with the same discharge and stage, pressure-flow induces much higher bed shear stresses at the bridge site, entailing an increased erosion potential. In these conditions, the flow acceleration around the piers and the lateral flow contraction have a lower impact on the erosive capacity, as confirmed by a pressure-flow simulation conducted by removing the piers.

How to cite: Lazzarin, T., Constantinescu, G., and Viero, D.: Eddy-resolving CFD modelling of a river flow at a full-scale, multi-pier bridge over naturally-deformed bathymetry, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6538, https://doi.org/10.5194/egusphere-egu24-6538, 2024.

Sustainable river management often requires long-term morphological simulations. As the future is unknown, uncertainty needs to be accounted for, which may require probabilistic simulations covering a large parameter domain. Even for one-dimensional models, simulation times can be long. One of the acceleration strategies is simplification of models by neglecting terms in the governing hydrodynamic equations. Examples are the quasi-steady model and the diffusive wave model, both widely used by scientists and practitioners. We established under which conditions these simplified models are accurate.

Based on results of linear stability analyses of the St. Venant-Exner equations, we assessed migration celerities and damping of infinitesimal, but long riverbed perturbations. We did this for the full dynamic model, i.e. no terms neglected, as well as for the simplified models. The accuracy of the simplified models was obtained from comparison between the characteristics of the riverbed perturbations for simplified models and the full dynamic model.

We executed a spatial-mode and a temporal-mode linear analysis and compared the results with numerical modelling results for the full dynamic and simplified models, for very small and large bed waves. The numerical results match best with the temporal-mode linear analysis. We show that the quasi-steady model is highly accurate for Froude numbers up to 0.7, probably even for long river reaches with large flood wave damping. Although the diffusive wave model accurately predicts flood wave migration and damping, key morphological metrics deviate more than 5% (10%) from the full dynamic model when Froude numbers exceed 0.2 (0.3).

How to cite: Barneveld, H., Mosselman, E., Chavarrias, V., and Hoitink, T.: Assessment of the Accuracy of Numerical Morphological Models based on Reduced Saint-Venant Equations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17212, https://doi.org/10.5194/egusphere-egu24-17212, 2024.

The Karnali River in Nepal bifurcates into two major branches (i.e., the eastern Geruwa branch and the western Kauriala branch), as it flows out from the Himalayan foothills onto a low relief area in southern Nepal, where it has created an alluvial fan of order 1000 km². Its dynamics are governed by the natural geomorphological processes of an alluvial fan. The eastern Geruwa branch, which until 2009 used to be the dominant branch regarding its share of the upstream water discharge, now receives a minor share of the water discharge. The reducing discharge in the Geruwa branch has decreased heterogeneity and suitability of wildlife habitat in its floodplains, which constitutes a significant area of Bardiya National Park. The dynamic river branches exhibit a high level of braiding, switching of the dominant channel, and an uneven discharge partitioning between the bifurcates. Our objective is to provide insight on how the system is affected by and will respond to anthropogenic interventions, especially the discharge distribution between the Geruwa and Kauriala branches. The switch in the flow partitioning since 2009 seems to be associated with an intense monsoon season. Besides this, embankments along the Kauriala branch, discharge intakes for irrigation, and unmanaged sediment mining may have affected the partitioning of flow and sediment flux over the Karnali River bifurcates. Furthermore, plans to develop multiple hydropower projects upstream will likely affect the system in the future. We study the impact of these factors on the discharge partitioning between the Geruwa and Kauriala branches, and in particular the flow rate in the eastern Geruwa branch, as the latter is the lifeline for wildlife in the Bardiya National Park, using field surveying/monitoring and numerical models. For this purpose, we have performed an intensive field campaign for data collection and have set up numerical models of various levels of complexity. We have measured cross-sectional profiles and spatial variation of the bed surface grain size distribution. Our observations reveal that bed level in the upstream Geruwa branch is higher than that of the upstream Kauriala branch. Furthermore, we observe river bend sorting in the bifurcation region, which results in a larger bed surface grain size in the upstream Geruwa branch. We have set up a one-dimensional hydrodynamic model to simulate the effects of interventions on the flow partitioning at the Karnali River bifurcation, as well as a two-dimensional hydro-morphodynamic model to study the impact of bend sorting and other two-dimensional aspects on the flow partitioning, as well as sediment deposition in and possible closure of the Geruwa branch.

How to cite: Gautam, K., Wolf, M., Ahmad, R., Bogaard, T., and Blom, A.: Dynamics of the Karnali River Bifurcation in Nepal , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18159, https://doi.org/10.5194/egusphere-egu24-18159, 2024.

Hydropower generation and the associated sediment management is one out of different water related services that are subjected to hydrological changes over time. Thus, the assessment and prediction of the sediment transported from catchments at varying temporal and spatial scales was and is an important task in hydraulic engineering. In this study, we focus on alpine catchments feeding a reservoir for hydropower production. Aim was to simulate and predict the suspended sediment input, which accounts for the vast majority of sediment loads.

The selected catchments, Pitzbach and Fagge, are part of the hydropower system Kaunertal Valley (Tyrol/Austria), operated by the TIWAG. The available measurements include discharges and turbidity/suspended solids contributing to the sedimentation of the Gepatsch reservoir. The discharge time series cover several decades, whereas turbidity was only measured during the recent years.

A combination of a process-based water balance modelling and a data driven approach to simulate sediment fluxes was combined to simulate extreme events and years as well as past periods where no material transport was measured.

For the two sub-catchments, different machine learning approaches were used to mimic suspended sediment transport, based on an available 11-year (2008-2018) long timeseries. Specifically, feed-forward neuronal networks (FFNN) and long short-term memory networks (LSTM), were tested and compared using different input combinations to identify the most suitable models for the respective catchment area.

For further validations the models were exanimated on a short “future” period (2019-2022), which was not part of the calibration. The model performance was evaluated for this time series, having a special focus on periods with exceptionally high transported sediment loads. For past periods (back until 1970), only discharge and reduced number of meteorological stations are available. Similarly, the models were applied to these periods in order to calculate sediment transport time series. On the one hand, a solely data driven approach using measured discharge and meteorological time series was tested. Beyond that, results from a process based hydrological model were used, aiming to cover also periods with gaps in the discharge data.

Overall, the simulations allowed to quantify the uncertainties associated to such modelling chains, when using them to describe sediment fluxes at different temporal scales.

How to cite: Frasnelli, T., Schöber, J., Pesci, M., Förster, K., and Achleitner, S.: Using machine learning approaches for predicting suspended sediments in alpine catchments – uncertainties and limitations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20292, https://doi.org/10.5194/egusphere-egu24-20292, 2024.

Estimations of sediment transport capacities and sediment connectivity are of high importance for water management at the catchment scale. Large-scale modelling techniques are helpful tools to give insights of such sediment budgets. However, these modelling techniques often require locally obtained characteristic values of the river sections, such as discharge measurements or river width values. Obtaining such information by in situ measurements or remote sensing data can get time- and cost-intensive, especially in remote and mountainous regions. Instead, several geospatial datasets with global coverage exist and can fill these gaps, if used adequately. We, therefore, adjusted the CASCADE model toolbox to work with freely available geospatial datasets as input parameters and exemplarily applied it to the Naryn River in Central Asia, which includes five artificial dam structures. The river characteristics such as slope and width were taken from the SWORD river database, and the hydrological information was taken from the Flo1K dataset. With the adjusted CASCADE model, we obtained information on sediment transport capacities in the catchment at the reach scale. As the model also accounts for sediment connectivity, we identified deposition- and erosion-prone areas and, therefore, localized sediment sinks and sediment sources in the catchment. The results showed that the large dams in the catchment influence the sediment budget significantly, for example by reducing the sediment transport capacities upstream, by trapping sediments in their reservoirs and by increasing the sediment entrainment downstream. Since sediment connectivity is an important parameter for ecosystem health and sustainable river management, such qualitative assessments of the sediment connectivity within large catchments can be helpful for prioritizing sediment management measures and be a basis for informed planning of more sustainable hydropower plants.

How to cite: Schwedhelm, H. and Rüther, N.: Analyzing Large-Scale Sediment Connectivity in a Central Asian Catchment Using Geospatial Datasets, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17002, https://doi.org/10.5194/egusphere-egu24-17002, 2024.

Water availability is not uniformly distributed, and water is not available on demand in many areas of the world. Thus, artificial storage of water is essential for the sustainable management of water resources. However, reservoirs are transport-limited systems due to low flow velocities, resulting in sedimentation. Additionally, global change amplifies sedimentation because of altered hydrological conditions and sediment production of river basins. Preparedness for global change necessitates decades-long forecasting of these complex phenomena, which is computationally challenging. Sediment depositions reduce not only the available storage volume over time but may create severe safety issues, such as blockage of bottom outlets or increased flood risk. Therefore, it is essential to understand not only the trapping efficiency of a reservoir and its temporal variations but also the spatial distribution of expected sediment accumulations. To generate these insights, long-term predictions based on three-dimensional (3d) hydro-morphological models considering the changing climate are required.

The Banja reservoir, located in southeast Albania, was investigated in this study to investigate the effects of global change on reservoir sedimentation. Simulations were performed up to 90 years into the future to model characteristic sedimentation stages and to test for differences between several emission scenarios, combined with socioeconomic and climate scenarios. A 3d numerical model simulated hydrodynamics, suspended sediment transport, and sedimentation processes, considering the Devoll River as the main tributary and three smaller tributaries. To enable long-term simulations, an adaptive grid with a spatial resolution of 50 m x 50 m in the x- and y-direction, respectively, as well as up to 10 cells in the z-direction was used. Due to an implicit time discretization a time step of 5,400 seconds was chosen to achieve reasonable computational times.

The model results showed a decrease in the trapping efficiency by 2100 for all scenarios, which is associated with storage loss over time. In the high and medium emission scenarios, the reservoir experiences a substantial loss of storage volume due to increasing sediment yields. The model also showed the formation of a delta at the head of the reservoir and the progressive movement of the delta further into the reservoir. These spatial and temporal insights into future sediment deposition patterns are crucial for developing sustainable management strategies to account for global change.

How to cite: Haun, S., Mouris, K., Schwindt, S., and Wieprecht, S.: Predicting global change effects on reservoir sedimentation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4113, https://doi.org/10.5194/egusphere-egu24-4113, 2024.

Reservoir sedimentation is a significant global challenge, including in India, for the sustainable management of vital hydraulic structures, impacting storage capacity, water demands, and ecological balances. The United Nations University - Institute on Water Environment and Health (UNU-INWEH) study has revealed that out of 47,403 large dams in 150 countries, the initial global storage of 6,316 billion cubic meters (BCM) is projected to decline to 4,665 BCM by 2050. This loss of 1,650 BCM is equivalent to the annual water use of India, China, Indonesia, France, and Canada combined. The report highlights the alarming decline in storage capacity across the globe.

The current study delves into the effectiveness of hydro-suction as a solution for reservoir desilting, exploring its applications through success stories and experimental investigations. Hydro-suction is a proven efficient method for sediment removal, avoiding disruptions to ecosystems and structures. This method utilizes suction forces to remove the sediment from the bed surface without interfering with the processing of the connecting structures such as irrigation canals and hydropower plants.

The study presents successful global applications of hydro-suction in desilting reservoirs, showcasing its effectiveness in real-world cases. The global success stories highlight diverse implementations and positive outcomes of the hydro-suction sediment removal method. In Djidiouia Reservoir, hydro-suction effectively removed 1.4×10⁶ m³ of silt and clay over two years, addressing rapid silting. Rioumajou Dam's hydro-suction system prevented sediment buildup, discharging 1 m³/s and paying off installation costs within a year. Tianjiawan Reservoir's hydro-suction system reclaimed storage capacity, removing 0.32×10⁶ m³ of sediment with a mean concentration of 15.6%. In Xiao Hua-shan Reservoir, sediment removal enhanced reservoir storage, hydropower generation, and downstream cropland topsoil quality. The Geolidro technique in Alpine reservoirs effectively removed over 5×10⁶ m³ of sediment in a span of 20 years. Further case studies include Alonia Lake's cost-effective sediment removal, California Reservoir's proposed hydro-suction system, Billings Lake's prevention of hydropower loss, and Palagnedra Reservoir's successful sediment removal despite limitations.

Along with the success stories, the current study also presents the interpretations from the experimental study done at the Indian Institute of Technology (IIT) Roorkee. The study systematically studied the area of influence of the suction force generated below the suction pipe during the hydro-suction by strategically changing the effective parameters, including suction pipe diameter, suction inlet height, suction discharge, and sediment median size, studied. A total of 252 experimental runs provide insights into the diameter and depth of influence below the suction pipe during hydro-suction. The analysis of diameter and depth of influence during hydro-suction experiments emphasizes the significance of suction inlet height and suction discharge. A Whisker's plot suggests an anticipated range of 2D to 3.5D for the diameter of influence and 0.5D to 0.8D for the depth of influence during hydro-suction sediment removal.

The case histories demonstrate the adaptability of hydro-suction in addressing sedimentation challenges across different regions. The experimental investigation would help plan and design the system for area-specific sedimentation removal. Hydro-suction can be a viable and environmentally friendly strategy for managing reservoir sedimentation.

How to cite: Jaiswal, A., Ahmad, Z., and Mishra, S. K.: Navigating reservoir sedimentation through hydro-suction, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4253, https://doi.org/10.5194/egusphere-egu24-4253, 2024.

Europe confronts a critical environmental challenge, with only one-third of its rivers meeting the “good ecological status” criteria of the EU Water Framework Directive as many river systems are impacted by damming and regulation. Our research focuses on the Myllykoski hydropower dam on Kuusinkijoki River, which has been operational since 1957. The hydropower dam is set to cease operations, marking a transformative step to restore the natural riverine environment. The cessation plan involves diverting water back to the long-unused Piilijoki River, reinstating its ecological role and improve the ecological status of the main Kuusinkijoki River that was disrupted post-dam construction. Our data collection strategy employed field campaigns, capturing high-flow conditions in spring, and low-flow conditions in autumn. Cutting-edge sensors were employed in this endeavour, utilizing the Otter Unmanned Surface Vehicle (USV) for underwater topography scans, Acoustic Doppler Current Profiler (ADCP) for flow characteristic measurements, and water level data loggers for monitoring water level time series. The collected data is then used to create a highly accurate seamless 3D map of the river channel and floodplain. Leveraging this intricate map, we deploy an advanced hydraulic model to comprehensively analyse hydraulic processes and assess flow characteristics following the planned halting of the Myllykoski hydropower dam. Our study's multifaceted objectives include evaluating the spatio-temporal variability of downstream flow in three distinct study sites: (a) an unused natural channel alongside the dam, (b) a man-made channel downstream, and (c) a natural channel downstream, including the riverine lake along the course of the Kuusinkijoki River. Furthermore, we aim to investigate the influence of various flow scenarios on downstream river flow characteristics, analyse spatio-temporal trends in flow dynamics, and identify any significant changes in response to the cessation of dam operations. A crucial aspect of our study involves evaluating the influence of dam halting on river hydrodynamics and ecology using modern sensors and analytical tools.

How to cite: Sadeqi, A., Kasvi, E., Marttila, H., and Alho, P.: Impact of Halting Dam Operations on Downstream Flow: A Modern Modelling Approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10441, https://doi.org/10.5194/egusphere-egu24-10441, 2024.

In the face of escalating climate change and an expected increase in extreme precipitation events leading to extreme floods, this work addresses the understudied but critical aspect of woody material in river systems. We aim to understand the dynamics of large woody debris during a severe flood and the evolution of floodplain vegetation in the periods between floods.

The study area is the River Alberche and its tributary, the River Perales (Tagus Basin, Central Iberian Peninsula). These were affected by an exceptional cut-off low weather situation (DANA in Spanish) in September 2023 producing heavy precipitation (up to 200 l/m²) and flash floods. This event flooded urban areas, damaged or destroyed four bridges, and resulting in two deaths. One of the damaged bridges had retained a significant deposit of large and fine woody material. After the flood, as usual, critical voices emerged from the affected population calling for the removal of woody material from the riverbeds. However, there are positive contributions of wood in rivers, enhancing hydro-morphological diversity and serving as a source of organic matter. Nevertheless, uncertainties remain regarding the dynamics and amounts of woody material, which warrant a comprehensive investigation.

This research aims to fill existing gaps by investigating the dynamics of woody material transport under these exceptional flow conditions through a post-event forensic survey. In addition, it aims to understand river bed vegetation during non-extreme flood periods. The knowledge generated will contribute to the development of basin-scale models that integrate woody material, thereby improving the accuracy of flood risk assessments and enabling the formulation of effective mitigation strategies.

How to cite: Lucía, A., Sandoval-Rincón, K. P., Vázquez-Tarrío, D., Garrote, J., Hernández-Ruiz, M., Perucha, M. Á., Romero, A., and Díez-Herrero, A.: Large wood recruitment and transport during a severe flash flood in Central Spain, September 2023., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18917, https://doi.org/10.5194/egusphere-egu24-18917, 2024.

Overland flow is a critical aspect of the hydrological cycle, and understanding its dynamics is crucial for managing water-related issues such as flooding and soil erosion. This paper investigates the impact of various roughness estimation methods on simulating overland flow during intense rain events, with a specific focus on the influence of vegetation height. The study assesses various approaches to vary roughness as a function of water sheet thickness and vegetation height, including two different constant Manning's coefficients, a simple linear approach, an exponential function, a power law function, an empirical formula, and a physics-based approach.

The investigation emphasizes the importance of accurate roughness estimation for improving the reliability of hydrological models and enhancing flood prediction capabilities. Experimental data from artificial rainfall experiments on 22 different natural hillslopes in Germany are used to calibrate the OpenLISEM hydrological model, adjusting parameters such as saturated hydraulic conductivity and soil suction at the wetting front.

Subsequently, various Manning's coefficient estimation methods are applied, and the model's performance is evaluated numerically. Preliminary results indicate satisfactory calibration outcomes, with NSE values ranging from 0.75 to 0.95 in most cases for various sites. To validate the models, 100 different experimental rainfall events are used for each roughness method.

Validation findings suggest that the physics-based approach, the linear function, and constant Manning roughness, demonstrate the best performance based on NSE values. According to our results, areas with more vegetation coverage demonstrate higher saturated hydraulic conductivity value, indicating that, for two sites with the same soil type, the locations with dense vegetation exhibit higher infiltration parameters. Consequently, it is crucial to evaluate the influence of vegetation on runoff, considering not only its effects on Manning's coefficient but also on saturated hydraulic conductivity.

This research contributes valuable insights into the selection of roughness estimation methods for enhancing the reliability of hydrological models, emphasizing the importance of vegetation cover in infiltration parameters.

How to cite: Masoodi, A. and Kraft, P.: Evaluating Vegetation-Influenced Roughness Estimation Methods to Improve Hydrological Modelling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10368, https://doi.org/10.5194/egusphere-egu24-10368, 2024.

Research on impacts of hydropeaking on river ecosystems has increased in the last years. For fish, much literature reports stranding and behavior changes, but physiological stress is less understood. In this study, we simulated a natural-flow scenario and five hydropeaking operating scenarios varying in frequency, duration and fall rate of the inundations, and water velocity and level in our Greenchannel facility, which is a mesocosm of fluvial ecosystem. 15 different rainbow trouts (Oncorhynchus mykiss) each time were subject to a scenario during 24 hours, measuring several physiological parameters at the end of the trials: Cortisol, CPK (Creatine Phosphokinase), LDH (Lactate Dehydrogenase), Triglycerides, Lactate, NEFA (Free Fatty Acids) and skin color. Results show how levels of these parameters change significantly in response to higher intensities of hydropeaking, which may lead to bad performance or death in the long term.

How to cite: Bejarano, M. D., Hernández-Marchena, R., De la Llave-Propín, Á., Bianucci, P., and Fazelpoor, K.: Hydropeaking on fish physiological stress, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20869, https://doi.org/10.5194/egusphere-egu24-20869, 2024.