GM2.1

Instrumented “smartrock” tracer clasts hold the potential to quantify unique and useful sediment transport statistics from the point of view of each grain--a Lagrangian reference frame.  In this presentation we synthesize lessons learned based on two successful smartrock field deployments in natural mountain rivers during snowmelt floods. Our sensors contain accelerometers, data loggers and batteries.  We have primarily used smartrock data to simply measure the exact timing of grain rests and motions, although future analyses and additional sensors could be used to measure many more aspects of transport.  In addition to methodological suggestions and challenges, we show how smartrock data can be used to measure (a) rest and hop time scaling over a range of timescales, and (b) changes in thresholds of motion through time as a function of discharge.  In data from Halfmoon Creek, Colorado, USA, and Reynolds Creek, Idaho, USA, rest duration scaling is heavy-tailed and varies systematically with both timescale and shear stress.  The shear stress dependence suggests that bedload clast dispersal becomes less superdiffusive as flood size becomes larger. We identify several likely diffusion regimes, and hypothesize how timescales of flow variability from turbulence to daily discharge cyclicity may cause scaling breaks over minutes to hours.  In addition, thresholds of motion tend to increase with cumulative flow (reducing transport rates over time), but also decrease with increases in discharge (increasing transport rates until grains restabilize at the higher flow). The threshold data are used to calibrate and partially validate a new model for discharge-dependent threshold evolution. Finally, we brainstorm ways in which smartrocks could be used to explore sediment transport questions in other Earth surface environments.

How to cite: Johnson, J., Pretzlav, K., Olinde, L., Bradley, D. N., and Masteller, C.: Rocks and Rivers that Remember:  Using Smartrocks To Constrain Bedload Transport Statistics and Evolving Thresholds of Motion in Natural Mountain Rivers, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9016, https://doi.org/10.5194/egusphere-egu22-9016, 2022.

An increase in storminess under climate change and population pressure are resulting in an increase in landslide and flood events, in the UK and globally, and threatening the defences put in place to mitigate these hazards. Monitoring of unstable hillslopes and flood-prone rivers as well as structures designed to protect these is vital. Furthermore, as landslides and floods are both triggered by heavy rainfall, often occurring simultaneously, and may interact to generate cascading hazards, we need integrated approaches for their management.

A key objective of the SENSUM project (Smart SENSing of landscapes Undergoing hazardous hydrogeomorphic Movement, https://sensum.ac.uk) is to develop a smart sensor to be embedded within boulder and wood debris in landslide and flood prone sites to detect and track hazardous movement. These low-power, low-cost devices communicate this in near real time via Internet of Things networks. Several wireless sensor networks (WSNs) have been installed on landslides and in flood-prone rivers around the UK, involving insertion of devices into debris, installation of long-range wireless network gateways, and camera installation for validation of movements. The developed system architecture also permits straightforward integration of additional third-party sensors and open data. We aim to build a dataset with which hazardous movement can be detected using machine learning and communicated in near real time via alerts and web services to relevant stakeholders. This effort will be complemented by laboratory experiments.

How to cite: Roskilly, K., Bennett, G., Curtis, R., Egedusevic, M., Jones, J., Whitworth, M., Dini, B., Luo, C., Manzella, I., and Franco, A.: SENSUM project, Smart SENSing of landscapes Undergoing hazardous hydrogeomorphic Movement, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10289, https://doi.org/10.5194/egusphere-egu22-10289, 2022.

The use of Inertial Measurement Units (IMUs) in geomorphological studies has exploded during the last decade. Scientists are deploying IMUs in a range of settings: from single grain flume experiments to full scale landslide motions and from capturing rock falls to measuring flows in glacial environments.

The vast majority of these experiments deploy sensing units that are partly customised for each application. However, there are limits to the level of IMU customisation geomorphologists can do as they rarely have access to bottom-up sensor assembly and production lines. Commercial IMUs and IMU components are built and calibrated for very different uses than the monitoring of dynamic sediment transport regimes, such as integration into electronic devices, wearables or Internet of Things applications.

Deploying commercial IMUs outside their nominal operational range has two main implications, the first being methodological. As the sensor is partly a "black box", we are obliged to do extensive testing in a trial-and-error manner and think deeply about the underlying physics of IMUs. If such difficulties are not acknowledged the results become difficult to interpret in the context of sediment movement.

The second implication concerns standardisation. The more our community uses commercial sensors and analytical tools, the more apparent becomes the need for open-source pre-processing and processing workflows that are fully validated and universally available to ensure comparability of published results.

This presentation aspires to contribute to this open debate about IMU sensors in geomorphology. The focus will be on the sensing requirements for grain motion detection, force capture and tracking by IMUs in the context of sediment transport. The presented calculations will use results published before the emergence of IMUs in geomorphology for a range of environments (fluvial, coastal, aeolian and glacial).

The above requirements capture will be accompanied by a meta-analysis of published IMU data in geomorphic applications which will be classified according to the exact type of sensor (accelerometer, full IMU, GPS (or equivalent)-aided IMU) and the sensors' specs (mainly sensing range and frequency).

Finally, this presentation will explore the case study of using a commercially available IMU for the capture of fluvial sediment interactions. The deployed IMU will be subjected to a series of simple physical experiments (e.g., drop tests) and then deployed to a flume setting designed to model grain-grain and grain-substrate collisions. The novelty here is the use of an independent very high-speed camera (1μs exposure frame rate) to monitor the sensor during calibration, which allows for the coherent propagation of uncertainty for all the experiments. All the results are presented within a processing workflow based on free, open-source R libraries.

How to cite: Gadd, C. and Maniatis, G.: Smart-pebbles in sediment transport studies: state of the art, future directions, and unsolved problems., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8757, https://doi.org/10.5194/egusphere-egu22-8757, 2022.

Woody debris dams/leaky dams are an increasingly popular Natural Flood Management (NFM) measure in low order tributaries, with preliminary evidence suggesting that they are effective in attenuating flood peaks and reducing flood risk. However, the stability of these dams is not widely monitored, and thus there is a poor evidence base for best design practice with respect to the long-term integrity of such features. This is particularly pertinent given the threat posed to downstream infrastructure by woody debris carried in floodwaters after potentially catastrophic dam failure. There is also a lack of research into how effective dams of different designs are at holding back large wood and sediment transported by the flow and reducing the impact of flood debris on downstream infrastructure, including bridges, culverts etc. In the SENSUM project (Smart SENSing of landscapes Undergoing hazardous hydrogeomorphic Movement, https://sensum.ac.uk), we are developing and applying innovative sensor technology to assess the stability of different woody debris dam designs and build an evidence base to inform policy on this NFM practice locally and nationally. We also use these sensors to track woody debris and assess how effective dams are at trapping and retaining large wood debris and cobble-sized sediment. This paper addresses these questions at several field sites across the UK and in laboratory experiments to report quantitative data which evaluate the literal success/failure of NFM interventions and how these may impact the future design of such approaches.

How to cite: Egedusevic, M., Bennett, G., Roskilly, K., Sgarabotto, A., Manzella, I., Raby, A., Boulton, S. J., Clark, M., Curtis, R., Panici, D., and Brazier, R. E.: Monitoring the stability of leaky dams and their influence on debris transport with innovative sensor technology on the SENSUM project, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8642, https://doi.org/10.5194/egusphere-egu22-8642, 2022.

Bedload transport is a fundamental process by which coarse sediment is transferred through landscapes by river networks and may be well described stochastically by distributions of grain step length and rest time obtained through tracer studies. To date, none of these published tracer studies have specifically investigated the influence of large wood in the river channel on distributions of step length or rest time, limiting the applicability of stochastic sediment transport models in these settings. Large wood is a major component of many forested rivers and is increasing due to anthropogenic ‘Natural Flood Management’ (NFM) practices. This study aims to investigate and model the influence of large wood on grain-scale bedload transport. 

We tagged 957 cobble – pebble sized particles (D₅₀ = 73 mm) and 28 pieces of large wood (> 1 m in length) with RFID tracers in an alpine mountain stream. We monitored the transport distance of tracers annually over three years, building distributions of tracer transport distances. Empirical data was used in linear mixed modelling (LMM) statistical analysis, determining the relative influence proximity to wood had on likelihood of entrainment, deposition, and the transport distances of sediments. 

Tracer sediments accumulated both up and downstream of large wood pieces, with LMM analysis confirming a reduction in the probability of entrainment of tracers closer to wood in all three years. Upon remobilisation, tracers entrained from positions closer to large wood had shorter subsequent transport distances in each year. In 2019, large wood also had a trapping effect, significantly reducing the transport distances of tracer particles entrained from upstream, i.e. forcing premature deposition of tracers. This study demonstrates the role of large wood in influencing bedload transport in alpine stream environments, with implications for both natural and anthropogenic addition of wood debris in fluvial environments.

How to cite: Clark, M., Bennett, G., Ryan, S., Sear, D., and Franco, A.: Capturing the Influence of Large Wood on Fluvial Bedload Transport with RFID Tracers and Linear Mixed Modelling, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2894, https://doi.org/10.5194/egusphere-egu22-2894, 2022.

Sand transport by wind displays dynamic structure and organisation in the form of streamers (aka ‘sand snakes’) that appear, meander and intertwine, and then dissipate as they are advected downwind. These patterns of saltating grain populations are thought to be initiated and controlled by eddies in the turbulent boundary layer airflow that scrape over the bed surface raking up sand into entrainment. Streamer behaviour is thus fundamental to understanding sand transport dynamics, in particular its strong spatio-temporal variability, and is equally relevant to granular transport in other geophysical flows (fluvial, submarine).

This paper presents findings on sand transport rates and streamer dynamics observed in a field experiment on a beach, by analysing imagery from 30Hz video footage, combined with 50Hz sand transport data from laser particle counters (‘Wenglors’), all taking place over an area of ~10 m² and over periods of several minutes.

Mapping of streamers and saltation cloud density is compared with fluctuations in sand transport rate measured at the Wenglors. Large-Scale Particle Image Velocimetry (LSPIV) is applied to determine advection vectors that can be matched against in-situ measurements of airflow and sand transport. Analysing video-imagery of aeolian sand transport faces several challenges, however, most notably the difficulties of background subtraction to differentiate the moving streamers from the underlying beach surface.

How to cite: Baas, A.: Video-Imagery Analysis of Aeolian Sand Transport over a Beach, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7639, https://doi.org/10.5194/egusphere-egu22-7639, 2022.

Bedload transport estimation is required for a variety of engineering and ecological applications. Measurement of bedload transport by direct sampling is expensive and time-consuming and rarely captures the spatio-temporal variability of bedload transport. Recent research shows that passive acoustic technology, such as hydrophone, has the potential to monitor bedload transport by recording Self Generated Noise (SGN) resulting from particles collision. In this work, we present a calibration curve relating specific bedload flux to cross-sectional acoustic power for 40 experiments conducted on 13 French rivers. We present the measurement protocols for bedload transport and SGN, the results of the campaign, and discuss the physics of the relationship between the measured quantities.

How to cite: Nasr, M., Geay, T., Zanker, S., and Recking, A.: Multi-river Calibration Curve for Passive Acoustic Bedload Transport Monitoring., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2505, https://doi.org/10.5194/egusphere-egu22-2505, 2022.

Bed load transport is a critical parameter in the study of landscape evolution and also provides valuable information for problems in the fields of ecology, river and landuse management, and civil engineering. Bed load transport is difficult to assess due to its stochastic nature and highly variable transport rates, and traditional measurement techniques have struggled to capture the spatial and temporal variability of bed load transport. In recent years, bed load monitoring based on seismological observations has emerged, which allows non-invasive and continuous indirect measurements. However, there still remains a significant challenge to independently characterise the seismic signature of bed load from other sources of noise, such as turbulence. Our study aims to explore seismic data recorded at the highly braided River Feshie in Scotland, which has undergone significant morphological change in its history and has been highly monitored over the last couple decades through Digital Elevation Models. Since the deployment of our seismometers in December 2020 we have captured three independent high flow events plus an isolated earthquake, which are being used to determine the environmental signals and the site specific signal characteristics. In some previous studies, an observed hysteretic relationship between seismic power and hydrological parameters has been interpreted as being characteristic of bed load transport. From the data we have gathered we have observed a hysteresis in the signals, and through Shields calculations it is suggested that bed load transport would be expected during these events. However, without independent constraints we do not feel we can be absolutely certain that this behaviour is a result of bed load transport. Our ongoing study therefore aims to combine multiple physical measurement techniques, such as hydroacoustic measurements, time-lapse imagery and seismic observations, to try and pinpoint what is contributing to the seismic signals recorded and how we can isolate the bed load transport component.

How to cite: Matthews, B., Naylor, M., Sinclair, H., Dietze, M., Williams, R., and Cuthill, C.: Isolating bed load transport from river induced seismic signals, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7633, https://doi.org/10.5194/egusphere-egu22-7633, 2022.

Flowing through the landscape, rivers generate high-frequency ground vibrations (> 1 Hz) by exerting force fluctuations on the bed. The well-established evidence that seismic sensors detect a wide variety of fluvial processes has motivated the use of seismology to indirectly measure sediment transport. In the last decade, numerous efforts have been dedicated to develop physically-based mechanistic models to investigate the link between the river-induced seismic signal and sediment transport properties such as the characteristic diameter of the transported sediments, bedload transport rate, debris flow thickness and velocity. However, most of the existing theories rely on simplistic descriptions of the transport dynamics that may not necessarily be sufficient to capture realistic behaviours. In particular, highly concentrated sediment flows are characterized by complex grain scale physical processes that could have a major impact on their seismic signature (Allstadt et al., 2020; Piantini et al., 2021).

Here, we carry out laboratory experiments to explore the seismic signature of highly concentrated sediment flows. Our scaled experimental setup allows the self-triggering and propagation of sediment pulses in a steep channel (slope of 18%), using a wide bimodal grain size distribution typical of mountain streams. We monitor physical parameters such as flow surface elevation, outlet solid discharge and the corresponding granulometric composition, together with seismically relevant quantities such as basal force fluctuations and flume vibrations using force and ultrasonic sensors, respectively. We observe transport conditions that range from the dilute transport of big grains (sediment pulse front) to dense sediment flows (sediment pulse body). Consistent with previous studies, the passage of the unsaturated front exerts the highest force fluctuations and seismic power. However, we also find that the body, despite having an amount of coarse particles similar to the front, becomes dramatically quieter when bulk density increases and the content of fine particles is maximum. We explain this latter behaviour by two main processes. First, flow stratification prevents a large part of the transported sediments from generating direct impacts to the fixed channel bed. Second, fines allow the formation of a conveyor belt that transport big particles with reduced collisions, as manifested by a considerable increase in their downstream velocity. These findings argue that internal stratification and the presence of a high content of fines may exert a major control on the seismic signature of highly concentrated sediment flows.

References

Allstadt, K. E., Farin, M., Iverson, R. M., Obryk, M. K., Kean, J. W., Tsai, V. C., Rapstine, T. D., and Logan, M.: Measuring Basal Force Fluctuations of Debris Flows Using Seismic Recordings and Empirical Green’s Functions, J. Geophys. Res.-Earth Surf., 125, 9, https://doi.org/10.1029/2020JF005590, 2020

Piantini, M., Gimbert, F., Bellot, H., and Recking, A.: Triggering and propagation of exogenous sediment pulses in mountain channels: insights from flume experiments with seismic monitoring, Earth Surf. Dynam., 9, 1423–1439, https://doi.org/10.5194/esurf-9-1423-2021, 2021

How to cite: Piantini, M., Gimbert, F., Korkolis, E., Rousseau, R., Bellot, H., and Recking, A.: What are the key elements that control the seismic signature of highly concentrated sediment flows?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8480, https://doi.org/10.5194/egusphere-egu22-8480, 2022.

Measuring the concentration and grain size of suspended sand in rivers continuously remains a scientific challenge due to its pronounced spatio-temporal variability. Vertical and lateral gradients within a river cross-section require spatially-distributed water sampling at multiple verticals and depths. However, this classical approach is time-consuming and offers limited temporal resolution. Sampling is particularly difficult in presence of a bimodal suspension composed of fine sediment and a sand fraction, notably if the fine/sand ratio varies with time. The aim of this study is to establish time series of sand concentration and grain size by improving temporal resolution using an acoustic multi-frequency method based on acoustic attenuation and backscatter to measure the suspension indirectly. Experiences of Moore et al. (2012) and Topping & Wright (2016) with Horizontal Acoustic Doppler Current Profilers (HADCPs) show that dual-frequency inversion can separate the fine sediment fraction dominating acoustic attenuation from the sand fraction dominating acoustic backscatter. Concentration and grain size of suspended sediment, both the fine and sand fraction, can be quantified by signal inversion after correction for transmission losses.

Applying existing dual-frequency, semi-empirical methods in a typical Piedmont river (River Isère, France) remains a challenge due to the high concentrations and a broad bimodal distribution. Two monostatic HADCPs of 400 and 1000 kHz were installed at a hydrometric station of the Isère at Grenoble Campus where discharge and turbidity have been recorded for more than 20 years. Using frequent isokinetic water samples obtained with US P-72 and US P-06 samplers close to the ensonified volume, a relation between acoustic signal and the sediment concentration and grain size can be determined. Simultaneously, total sand flux and grain size distribution are calculated performing solid gaugings using Delft bottle samples and ADCP measurements in the entire cross-section. The method using index concentration and grain size in the HADCP measurement area is then used to evaluate the total sand flux and average grain size time-series in the cross-section.

First results show good correlations between the fine sediment concentration and the sediment attenuation for both frequencies. Specific extreme events (e.g. debris flows, dam flushes or spring floods) show distinct signatures in acoustic attenuation, backscatter and ratio between the two frequencies. During a debris flow (concentration up to 5.3 g/l), attenuation reached 1.6 and 3 dB/m for 400 respectively 1000 kHz, but no peak in backscatter intensity, whereas a spring flood (up to 4 g/l with at least 50 % sand) caused major peaks in attenuation and backscatter. Pronounced hysteresis during the events and time-varying ratio between attenuation due to sediments measured by 400 and 1000 kHz indicate suggest that the grain size distribution may vary. Relating sand concentration from physical samples with beam-averaged backscatter may elucidate changes in grain size more precisely. Existing heterogeneities of concentration and grain size along the acoustic beam contradict the homogeneous distribution supposed by the method and require local analysis based on local concentration and grain size characteristics.

How to cite: Laible, J., Camenen, B., Le Coz, J., Dramais, G., Lauters, F., and Pierrefeu, G.: Establishing time series of flux and grain size of suspended sand in rivers using an acoustic method, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7344, https://doi.org/10.5194/egusphere-egu22-7344, 2022.

The size distribution of sediments together with their shape inform on their transport history, are important factors controlling the efficiency of erosion and transport, and control the quality of aquatic ecosystems. However, the size distribution of sediments is generally assessed using poorly representative field measurements and determining the grain-scale shape of sediments remains a real challenge in geomorphology. To tackle this issue, we develop a new methodological approach based on the segmentation and geomorphological fitting of 3D point clouds. Point cloud segmentation into individual grains is performed using a watershed algorithm applied here to 3D point clouds. Once the grains are individualized into several sub-clouds, the morphology of each grain is determined by fitting a 3D ellipsoid to each sub-cloud. These 3D models are then used to extract the size distribution and the grain-scale shape of the sediment population. The algorithm is validated against field data acquired by Wolman counts in coastal and fluvial environments. The main benefits of this automatic and non-destructive method are that it provides, with a fast and efficient approach, access to 1) an un-biased estimate of surface grain-size distribution on a large range of scales, from centimeters to tens of meters; 2) a very large number of data, only limited by the number of grains in the point-cloud dataset; 3) the 3D morphology of grains, in turn allowing to develop new metrics characterizing the size and shape of grains; and 4) the in-situ orientation and organization of grains and grain clusters. The main limit of this method is that it is only able to detect grains with a characteristic size significantly greater than the resolution of the point cloud.

How to cite: Guerit, L., Steer, P., Lague, D., Crave, A., and Gourdon, A.: Fast and automatic measurement of grain geometries from 3D point clouds, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6321, https://doi.org/10.5194/egusphere-egu22-6321, 2022.

The structure and function of rivers is directly related to bedload transport which is difficult to measure due to its spatial heterogeneity and the logistic constraints of field measurements. These difficulties have given rise to the morphological method wherein sediment transport is inferred from changes in morphology and estimates of the distance traveled by sediment during a flood, its path length. However, current methods for estimating path length are time and labor intensive, have low recovery rates, and are limited to some morphological units. We propose a method to estimate path length from repeat digital elevation models (DEM’s of difference i.e. DoDs) which are requisite for the morphological method. We interpret the pattern of erosion and deposition downstream as a signal and apply Variational Mode Decomposition (VMD), a signal processing method, to quantify the periodicity as a proxy for path length. We developed this method using flume experiments with measured sediment flux and applied it to published field data with tracer measurements for validation. The preliminary results provide a range of values on the same order of magnitude as measured tracer and flux data and are coherent with channel geometry. This method provides a reasonable estimation of path length based solely on remotely sensed data and a range of plausible sediment fluxes associated with specific channel morphological processes through DoD interpretation.

How to cite: Capito, L., Bizzi, S., Surian, N., and Bertoldi, W.: Particle path length estimation: a signal processing approach, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1378, https://doi.org/10.5194/egusphere-egu22-1378, 2022.

Today, erosion is increasing in many intensively used agricultural regions with fertile soils. At the same time, scientists expect that the intensity of heavy precipitation events, their erosivity, drought intensity and persistance will increase significantly through climate change. In combination with more strict regulations to protect the natural environment from nutrients and hazardous substances (such as herbicides and micro-plastics), it is challenging to balance the interests of food (and energy) production and environmental protection.

Therefore, we design and establish a worldwide unique measurement plot at the Bavarian Agricultural Institute (LfL) to assess different combinations of four- and six-year crop rotation schemes and machining methods concerning their long-term soil fertility, stability and resilience against climate change effects and environmental impacts, focusing on compound effects. The plot to measure and compare soil-water retention, nutrient fluxes, surface runoff, and erosion masses has an area of four acres and 14 parallel crop strips. Crop cultivation, experiments and measurements with and without artificial rain will be performed for more than ten years after a three-year set-up phase, will have a 4D (3D spatial plus temporal) high-resolution design and combine established and innovative measurement and management techniques, such as artificial intelligence, neural networks, deep learning, and robotics. Finally, up-to-date process-based hydrological modelling will incorporate the measurement data to increase our process understanding and enable upscaling to catchment scales.

This contribution to EGU 2022 will inform and include the scientific community during the set-up phase about the running and planned activities to build an international scientific network, discuss our approaches, efficiently use the existing scientific knowledge, and initiate future collaborations around the measurement financed by the German federal state of Bavaria.

How to cite: Ebertseder, F., Mitterer, J., and Disse, M.: Moving the frontier of comparative erosion measurements under different agricultural schemes – Development of a long-term, high-resolution, 4D erosion measurement site of the Bavarian Agricultural Institute in Lower Bavaria (Germany), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9500, https://doi.org/10.5194/egusphere-egu22-9500, 2022.

Abstract: Climate change and land-use change impact the sediment flux and grainsize delivered to rivers which influences channel morphologies and hence modifies flood risk; this is particularly the case where channels are fed by high mountain catchments. Here, We studied the Nakkhu River which is the largest southern tributary of the Kathmandu basin, Nepal. The mobility of the channel is well documented in response to bank erosion, down-cutting, and accumulation of bar forms; these processes are particularly important during extreme flood events. Comparing satellite images from 2003 to 2020, the river course, which has a medium channel width of 15 m, has migrated laterally up to 130m. Bank erosion and down-cutting reduce the inundation and water storage upstream, whereas aggradation of river bar forms downstream reduces the channel’s conveyance capacity. These vertical and lateral geomorphological alterations result in significant impact on flood risk downstream.

In this research, we investigate how changes in sediment supply, and grain size affect river morphology and flood inundation in the Nakkhu River. We use the landscape evolution model, CAESAR-Lisflood, combined with a newly generated (2019) 10 m digital elevation model, field-derived grainsize data and 20 years (2001 to 2020) of daily discharge data, to simulate erosion and deposition along a 14 km reach of the river. In a set of experiments, we compare river bed cross-sections, flood extent, and water depths for 15 model scenarios where we vary sediment supply and grain size from fine sand to coarse gravel dominated distributions assessing the geomorphic uncertainty of observation of sediment data.

The model results show that channel morphologies are sensitive to changes in sediment grainsize distribution. The study suggests that lack of consideration of sediment impact in flood hazard mapping could lead to increased flood risk. In addition, this study highlights some of the challenges regarding the significance of grain size parameter and uncertainty to the landscape evolution model that need to be addressed in current research.

Keywords: River morphology, sediment flux, grainsize, flood modelling, Nepal

How to cite: Thapa, S., Sinclair, H. D., Creed, M., Mudd, S. M., Attal, M., Muthusamy, M., and Sharma, B.: Modelling the sensitivity of changes in sediment flux and grainsize distributions on flooding in the Kathmandu basin, Nepal, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6865, https://doi.org/10.5194/egusphere-egu22-6865, 2022.

Seismic shaking in mountain environments introduces the potential for complex fluvial response from a multitude of landslide sources. Stream networks may be impacted in multiple branches, introducing the possibility of interacting sedimentary ‘pulses’ moving through the system. Large quantities of mobile sediment added to the stream network from multiple sources during and after a co-seismic event can overload susceptible river reaches, causing changes in sediment transport and storage. Although past research works have addressed dynamic sediment movement in river networks and identification of sedimentary hotspots, the physiographic factors (e.g. canyons, bends, fans, slope change) that prompt such change remain unexplored. The catchment settings and reach sequences that contribute most to delay/acceleration of the sediment in the active mountain environments are investigated in order to improve hazard assessment in susceptible terrain. In this work, we employ the one-dimensional River Network Bed-Material Sediment model (Czuba & Foufoula-Georgiou, 2014) to explore the landscape factors that may lead to hotspot behaviour for the very coarse sand fraction (2mm), followed by multi-criteria analysis of four basic stream network parameters: slope, sinuosity, channel confinement and tributary influence. Patterns of network topology associated with delay and accumulation of river sediment in the model were systematically identified in 75,400 stream links from 16 major drainages (135 to 6425 km²) of New Zealand’s upper South Island, as assessed by sediment travel time and the cluster persistence index (CPI). Catchment size determines the number of sediment sources, and thus ultimately the magnitude of the sedimentary hotspots i.e., bigger catchments can accommodate more landslides which increases the sediment input, along with the chances of sediment accumulation at susceptible locations. Multi-criteria analysis of the top 10 reaches with highest CPI values in each catchment (160 sites, total), showed that about 30% of the hotspots occurred in partly-confined valley settings with gentle slope (<0.02m/m), moderate sinuosity (1-1.1), downstream from the confluence of two or more tributaries. This combination emerged as the most likely setting for the occurrence of sedimentary hotspots in active mountain river networks. This approach may provide a simple means to map out susceptible sites based upon reach characteristics, which will not only contribute to improved catchment hazard assessment but may also help to augment more sophisticated models of catchment response to co-seismic landslide events.

How to cite: Tamang, N. B. and Tunnicliffe, J.: Network-scale analysis of sedimentary hotspots in dynamic, seismically-active steepland rivers, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1395, https://doi.org/10.5194/egusphere-egu22-1395, 2022.