Suspended Sediment Concentration Data Research Articles

Machine‐Assisted Physical Closure for Coarse Suspended Sediments in Vegetated Turbulent Channel Flows

AbstractThe parameterization of suspended sediments in vegetated flows presents a significant challenge, yet it is crucial across various environmental and geophysical disciplines. This study focuses on modeling suspended sediment concentrations (SSC) in vegetated flows with a canopy density of avH ∈ [0.3, 1.0] by examining turbulent dispersive flux. While conventional studies disregard dispersive momentum flux for avH > 0.1, our findings reveal significant dispersive sediment flux for large particles with a diameter‐to‐Kolmogorov length ratio when dp/η > 0.1. Traditional Rouse alike approaches therefore must be revised to account for this effect. We introduce a hybrid methodology that combines physical modeling with machine learning to parameterize dispersive flux, guided by constraints from diffusive and settling fluxes, characterized using recent covariance and turbulent settling methods, respectively. The model predictions align well with reported SSC data, demonstrating the versatility of the model in parameterizing sediment‐vegetation interactions in turbulent flows.

The effectiveness of alluvial gully remediation in Great Barrier Reef catchments

This study presents data from a large-scale Before After Control Impact (BACI) design field experiment that measured the sediment reduction achieved by remediating large alluvial gullies. The study was carried out on Bonnie Doon Creek on the lower Burdekin River, in Queensland Australia. Prior to remediation, the four large alluvial gully complexes (active area of ∼17ha) were conservatively estimated to be delivering 5800 ± 1500 t of fine sediment (<20 μm) per year (20 year average). The experiment demonstrated that the average remediation effectiveness across 10 different treatments was a 96%–99% reduction in fine sediment yield (or an annualised reduction of ∼5500t). High resolution lidar DEM of Difference (DoD) derived sediment yields in the unremediated gullies were found to be, on average, 58% lower than yields derived from monitored suspended sediment concentration (SSC) data, albeit with some uncertainty. These data support the notion that even high resolution (0.1m) lidar DoD yields are missing erosion driven by rainfall driven downwearing across all internal gully surfaces that is below the limit of detection (LOD) of the lidar. The results highlight that the greatest uncertainty in predicting the sediment abatement from gully remediation is associated with the determination of the baseline sediment yield of each gully. Future research effort should be focused on improving our understanding of baseline (multi-decadal) sediment yields, and monitored (annual) yields in different types of unremediated gullies. This is dependent on developing a detailed understanding of how these gullies evolve through time, and what the processes are that drive ongoing gully growth.

Longitudinal Recovery of Suspended Sediment Downstream of Large Dams in the US

AbstractDams disrupt the natural flow of water and sediment along rivers. Reservoirs trap a significant amount of sediment, which substantially alters downstream hydrology, channel morphology, and sediment transport capacity. The longitudinal recovery of suspended sediment concentration (SSC) along rivers is potentially a new metric for estimating downstream responses to dams over space, rather than time, but is rarely quantified due to the lack of spatial SSC data. Satellites can estimate SSC along rivers where no field data exist and provide a high enough spatial resolution for assessing downstream recovery at the scale of tens to hundreds of kilometers. Here, we use a recently published database of spatially explicit SSC observations derived from Landsat to quantify if a river recovers or not, the SSC recovery percentage, and SSC recovery length downstream of large dams across the Contiguous United States (CONUS). Rivers recover SSC downstream of most dams (71%). The chance of a river recovering and the length of river required to recover SSC is associated primarily with the size of the reservoir (mean storage, km3) and the size of the river (mean discharge, m3/s). Rivers were more likely to recover SSC downstream of run‐of‐river, navigation dams compared to large storage or hydropower dams. Our results suggest that rivers typically recover suspended sediment downstream of dams, influenced by factors like dam storage, purpose, and river channel characteristics.

Deep Learning-Based Simulation of Surface Suspended Sediment Concentration in the Yangtze Estuary during Typhoon In-Fa

Effectively simulating the variation in suspended sediment concentration (SSC) in estuaries during typhoons is significant for the water quality and ecological conditions of estuarine shoal wetlands and their adjacent coastal waters. During typhoons, SSC undergoes large variations due to the significant changes in meteorological and hydrological factors such as waves, wind speed, and precipitation, which increases the difficulty in simulating SSC. Therefore, in this study, we use an optimized Principal Component Analysis Long Short-Term Memory (PCA-LSTM) framework with an attention mechanism to simulate the SSC in the Yangtze Estuary during Typhoon In-Fa. First, we integrate data from different sources into a multi-source dataset. Second, we use the PCA to reduce the dimensionality of the multi-source data and eliminate redundant variables in the feature data. Third, we introduce an attention mechanism to optimize the long and short-term memory (LSTM) model. Finally, we use the differential evolution (DE) algorithm for hyperparameter selection and merge the feature data with the SSC data as the input of the optimized LSTM network to simulate SSC. The results showed that SSC’s fitting coefficients (R2) at four hydrological stations improved by 7.5%, 6.1%, 7.4%, and 7.8%, respectively, using the attention-based PCA-LSTM compared to the PCA-LSTM. Moreover, compared to the traditional LSTM model, the R2 was improved by 33.8%, 30.5%, 32.0%, and 28.6%, respectively, using the attention-based PCA-LSTM framework. The study indicates that the selection of input variables can affect the model results. Introducing an attention mechanism can effectively optimize the PCA-LSTM framework and improve the simulation accuracy, which helps simulate the non-linear process of SSC variation occurring during Typhoon In-Fa.

Estimation of daily suspended sediment concentration in the Ca River Basin using a sediment rating curve, multiple regression, and long short-term memory model

Abstract This study presents a sediment rating curve (SRC), multiple regression (MR), and long short-term memory (LSTM) model for estimating daily suspended sediment concentration (SSC). The data of daily SSC at Yen Thuong and daily flow at five locations in the Ca River Basin, Vietnam are used to demonstrate multiple approaches. Using the daily flow and SSC data in the period from 2009 to 2019, appropriate coefficients in each method are identified carefully using five popular criteria. The results showed that SRC and MR approaches reproduced acceptably the observed values, with the values of RMSE, MAE, and ME of daily SSC being less than 5% of daily SSC magnitude observed at the station, while NSE ranges from 0.47 to 0.63 and r coefficient varies between 0.69 and 0.80. The LSTM model represented the observed values of daily SSC very well. The values of two dimensionless criteria are greater than 0.94 and its values of three-dimensional criteria are smaller than 2.0% of the observed magnitude of daily SSC in both training and validation steps. The LSTM model is found to be the best among the three investigated approaches. Then, the model is applied to estimate daily SSC values for the period from 1969 to 2008 and the year 2020.

Riverine Microplastic Quantification: A Novel Approach Integrating Satellite Images, Neural Network, and Suspended Sediment Data as a Proxy

Rivers transport terrestrial microplastics (MP) to the marine system, demanding cost-effective and frequent monitoring, which is attainable through remote sensing. This study aims to develop and test microplastic concentration (MPC) models directly by satellite images and indirectly through suspended sediment concentration (SSC) as a proxy employing a neural network algorithm. These models relied upon high spatial (26 sites) and temporal (198 samples) SSC and MPC data in the Tisza River, along with optical and active sensor reflectance/backscattering. A feedforward MLP neural network was used to calibrate and validate the direct models employing k-fold cross-validation (five data folds) and the Optuna library for hyperparameter optimization. The spatiotemporal generalization capability of the developed models was assessed under various hydrological scenarios. The findings revealed that hydrology fundamentally influences the SSC and MPC. The indirect estimation method of MPC using SSC as a proxy demonstrated higher accuracy (R2 = 0.17–0.88) than the direct method (R2 = 0–0.2), due to the limitations of satellite sensors to directly estimate the very low MPCs in rivers. However, the estimation accuracy of the indirect method varied with lower accuracy (R2 = 0.17, RMSE = 12.9 item/m3 and MAE = 9.4 item/m3) during low stages and very high (R2 = 0.88, RMSE = 7.8 item/m3 and MAE = 10.8 item/m3) during floods. The worst estimates were achieved based on Sentinel-1. Although the accuracy of the MPC models is moderate, it still has practical applicability, especially during floods and employing proxy models. This study is one of the very initial attempts towards MPC quantification, thus more studies incorporating denser spatiotemporal data, additional water quality parameters, and surface roughness data are warranted to improve the estimation accuracy.

Multiscale Spatio‐Temporal Variations of Suspended Sediment Fronts in the Semi‐Enclosed Bohai Sea, China

AbstractSuspended sediment fronts (SSFs) significantly affect water quality, ecology, and geomorphological evolution of estuarine and coastal waters. Based on 10‐year suspended sediment concentration data derived from satellite images, the multiscale spatio‐temporal variability of SSFs in the Bohai Sea was studied. Frontal probability (FP) was used to quantify the intensity of frontal activity. The 10‐year averaged FP was higher near the coast and decreased with increasing offshore distance. The arc‐shaped distributions of FP near the Yellow River Estuary revealed two tidal shear frontal zones. In the eastern Bohai Sea, 13 finger‐shaped high‐FP areas reflected the spatial pattern and fine structures of tidal sand ridges. The complex topography and strong tidal dynamics provided the essential conditions for frontogenesis. The seasonality of frontal activity was dominantly regulated by the change in wind waves associated with monsoons and stratification. The direct or indirect effects of sediment discharges from the Yellow River and Liaohe River on seasonal and annual variations of frontal activity only existed within close proximity to the estuaries. Frontal activity generally showed an interannual weakening trend, especially in the Laizhou Bay (−0.27%/yr), while an opposite trend was identified in the Liaodong Bay (0.10%/yr). This phenomenon was related to the interannual variations of wind speeds. Meanwhile, wind speed anomalies caused by El Niño‐Southern Oscillation events could explain the significant interannual fluctuations in frontal activity such that, frontal activity was significantly enhanced (suppressed) when El Niño (La Niña) events occurred, especially during 2015–2016 (2017–2018).

Hydrological and sediment-transport characteristics of the middle and lower Yangtze River: Analysis from a magnitude-frequency perspective

In natural quasi-equilibrium rivers or anthropogenically-influenced nonequilibrium rivers, the occurrence frequency and sediment transport capacity of different flow levels are greatly important to understanding the linkage between forms and processes. However, our knowledge of the controlling factors on flow frequency and sediment-transport magnitude in large river systems remains limited. In this paper, the hydrological and sediment-transport characteristics of the middle and lower Yangtze River (MLYR) were systematically examined before and after impoundment of the Three Georges Reservoir (TGR). More than 30 years of daily discharge and suspended sediment concentration data were collected from six hydrological stations. The results showed that in the pre-TGR period, the flow frequency distributions (FFDs) and sediment-transport rating curves had segmentation characteristics. Generally, the FFDs of medium-high flow agreed well with the broken power law, and the sediment-transport rating curves deviated from the power law at high flow. This was because the floodplains, especially the Dongting Lake, had significant effects on flood attenuation and sediment storage. Compared the inflection points of the FFD and the sediment-transport rating curve, as well as the effective discharge and bankfull discharge, these four values were of the same order of magnitude. This suggested that the local river system had a dominant effect on the hydrological and sediment-transport characteristics. In the post-TGR period, the overall characteristics of the FFDs were preserved, but the segmental characteristics of the sediment-transport rating curves at higher discharges disappeared. Through analysis, the effective discharge was largely determined by the inflection value (a1) of the FFD. The reduced a1 induced a 10%–20% decrease in effective discharge, which indicated flood channel shrinkage in the long run. These findings not only further the understanding of water-sediment regimes in a large alluvial river with an extensive floodplain system but also offer guidance for improving dam operation schemes for river restoration.

Comparative analysis of discharge and sediment flux from two contiguous glacierized basins of Central Himalaya, India

In the present study, suspended sediment load (SSL), sediment yield and erosion rates in Pindari Glacier basin (PGB) and Kafni Glacier basin (KGB) have been estimated using daily discharge and suspended sediment concentration (SSC) data for three ablation seasons (2017-2019). For this, one meteorological observatory and two gauging sites have been established at Dwali (confluence point), and water samples have been collected twice in a day for high flow period (July to September) and daily for lean period (May, June and October). An area-velocity method and stage-discharge relationship has been established to convert water level into discharge (m3 s-1). For estimating SSC (mg/l), collected water samples have been filtered, dried, analysed and confirmed with an automatic suspended solid indicator. Further, SSL, sediment yield and erosion rates have been computed using SSC data. The results reveal that mean annual discharge in PGB (35.06 m3s-1) has been found approximately 1.7 times higher than KGB (20.47 m3s-1). The average SSC and SSL in PGB have been observed about 396.07mg/l and 1928.34 tonnes, and in KGB, it is about 359.67mg/l and 1040.26 tonnes, respectively. The SSC and SSL have followed the pattern of discharge. A significant correlation of SSC and SSL has been found with discharge in both the glacierized basins (p < 0.01). Interestingly, average annual sediment yield in PGB (3196.53 t/km2/yr) and KGB (3087.23 t/km2/yr) have been found almost identical. Likewise, the erosion rates in PGB and KGB have been witnessed about 1.18 and 1.14mm/yr, respectively. Sediment yield and erosion rates in PGB and KGB have been found in correspondence with other basins of Central Himalaya. These findings will be beneficial for engineers and water resource managers in the management of water resources and hydropower projects in high-altitude areas and in the planning and designing of water structures (dams, reservoirs etc.) in downstream areas.

Contrast of fine sediment dynamics between shoals and channels in a microtidal estuary with mixed semi-diurnal tides

Estuaries usually feature complex bathymetries, where shoals and channels are co-existent. Due to the differences in water depth, current, density gradient and therefore stratification, sediment dynamics on the shoal and in the channel demonstrate significant variations. In this study, field measurements were carried out during spring and neap tides in both wet and dry seasons in the Huangmaohai Estuary, a microtidal estuary located in the southwest of the Pearl River Delta. Harmonic analysis was conducted for the timeseries data of current and suspended sediment concentration (SSC) for each deployment. Sediment transport flux was decomposed into an advective component, and tidal pumping fluxes by different tidal constituents. During the neap tides, sediment transport is primarily controlled by the advective flux, whereas during the spring tides, tidal pumping fluxes become comparable to, sometimes even exceeding, the advective one. For a 25-hr period, the M1 component of SSC usually denotes the maximum SSC associated with the highest bottom stress, while the M2 component signifies the two highs of the SSC. The M4 component is generally insignificant. The M1 and M2 components can be induced by both the advection and bottom resuspension. For the resuspension part, the M1 component is mostly induced by tidal velocity asymmetry, while the M2 component is generated by tidal straining effect. Sediment transport at the shoal is mostly controlled by the advective flux and the tidal pumping due to tidal velocity asymmetry, while that in the channel is dictated by advective transport and the tidal pumping due to tidal mixing asymmetry.

Abordagem de discretização para modelagem de sedimentos em grande escala: estratégias de calibração baseadas na variabilidade hidrossedimentológica em múltiplas escalas espaciais

ABSTRACT The lack of observed data and calibration strategies, scale variability, and difficulties in representing heterogeneity of sediment-processes contribute to the usual challenges in achieving satisfactory results in hydro-sedimentological modeling, particularly when using the MUSLE equation for large-scale applications. As a consequence, we investigated five major topics: (1) a sediment-process-based parameterization technique (Hydro-sedimentological Response Unit map - HRUSed); (2) the quality of hydrological modeling with different process-focused parameterizations; (3) a calibration strategy based on the sediment discretization approach for hydro-sedimentological modeling; (4) the use of suspended sediment concentration (SSC) versus suspended sediment discharge (SSD) data for calibration; and (5) trade-offs between increasing the spatial resolution of a large-scale model and using the proposed HRUSed discretization. The current study demonstrated (1) the HRUSed map for South America and (2) a similar performance of large-scale hydrological modeling using a hydrological or hydro-sedimentological discretization approach. (3) The HRUSed discretization approach produced better hydro-sedimentological modeling results. (4) We improved the model’s performance for HRUSed (SSC and SSD results) and for HRU (Hydrological Response Unit map) only for SSD results. (5) Only more detailed spatial discretization has failed to improve process representation. However, increased spatial discretization with a process-parameterization approach focused on hydro-sedimentological dynamics improved model performance.

Spatio‐Temporal Variability of Suspended Sediment Fronts (SSFs) on the Inner Shelf of the East China Sea: The Contribution of Multiple Factors

AbstractModulated by a host of complex processes, suspended sediment fronts (SSFs) on the inner shelf of the East China Sea persist strongly and vary notably. Using hourly suspended sediment concentration data collected by the Geostationary Ocean Color Imager over the period 2011–2021, a gradient‐based edge detection algorithm was implemented to extract SSFs; the frontal probability (FP) and seasonal and interannual variability were identified and interpreted. Pronounced frontal activity is principally confined to the nearshore waters within the 60‐m isobaths and decreases with increasing offshore distance. Frontogenesis is mainly determined by the bottom topography and tide‐induced mixing. Empirical orthogonal function decompositions reveal that the seasonal cycle dominates the variability of SSFs, which responds to the cycles of winds and related changes in coastal currents and upwelling. The highest FPs are identified in winter when wind‐induced suspended sediment transport and resuspension reach their annual maxima. In summer, stratification and the intrusion of Kuroshio subsurface water are not conducive to frontogenesis. Furthermore, the discharge of the Yangtze River has a certain influence on the frontal variability in the waters around the Zhoushan Archipelago. Notably, the interannual variability of SSFs is modulated by the El Niño‐Southern Oscillation. These findings, based on a comprehensive dataset of SSFs over 10 years, can usefully inform the studies of marine pollutant transport, sedimentary dynamics, fisheries, and wider ecological processes in the study area.

Variations in the Suspended Sediment Concentration in Mountain-Type Rivers Flowing Into the Sea in the Past 60 years—Taking Nanliu River in Beibu Gulf as an Example

Suspended sediment in the water body of rivers flowing into the sea is of great significance to the accumulation process in river basins and change pattern of landforms. In particular, small and medium rivers entering the sea in mountainous areas exhibit the characteristics of both mountains and streams, and the suspended sediment concentration (SSC) greatly contributes to the formation and evolution of deltas. However, scholars rarely give attention to the factors influencing changes in the SSC in small- and medium-sized mountainous rivers, and few studies have examined SSC changes in small- and medium-sized mountainous rivers. Here, based on daily SSC and flow data obtained at the Bobai Station and Changle Station, the percentile method and regression analysis method are employed to analyse the changes in SSC from the Nanliu River to the Beibu Gulf and possible influencing factors. The main research results indicate that 1) the SSC in river water bodies from 1965 to 2020 generally reveals a downwards trend, with significant annual variations. Specifically, the overall trend can be divided into three stages: 1) the SSC is the highest from 1965 to 1971, and the mean yearly SSC reaches 0.25 kg/m3; 2) the SSC is relatively high from 1972 to 2006, and the mean yearly SSC reaches 0.16 kg/m3; and 3) the SSC is the lowest from 2007 to 2020, and the mean yearly SSC reaches 0.11 kg/m3 2) High values of the SSC are mainly concentrated in the flood season, and low SSC values mostly occur in the dry season. The monthly average SSC in the flood season from April to September and the dry season from October to March exhibits the characteristics of a decrease in the flood season and an increase in the dry season. Moreover, the peak SSC value in the watershed obviously occurs out of sync with the peak flow value. Generally, the former precedes the latter. 3) The curve of the flow rate-sediment ratio is an irregular clockwise rhombus. Moreover, the impact of tropical cyclones, land cover changes, regional GDP per capita, and engineering construction are crucial reasons for the observed variations in the SSC in the Nanliu River Basin. In this paper, the obtained research results provide an important guiding significance for the planning and management of water and sediment resources in the Nanliu River and offer a reference for hydrological planning of other river basins discharging into the sea.

Predicting the potential impact of forest fires on runoff and sediment loads using a distributed hydrological modeling approach

Forest fires profoundly affect the nature of watershed responses to precipitation, increases in runoff rate and volume, and post-fire sediment discharge. A post-fire watershed assessment to identify potential trouble spots for soil erosion and flooding can help land managers for decision-making on deploy mitigation, remediation measures, and restoration action plans. Predicting the potential impact of fires on runoff and soil erosion requires distributed hydrological modeling methods. This study used the Soil and Water Assessment Tool (SWAT), a rainfall-runoff model, to investigate the hydrological consequences of forest fires and their impact on sediment load under different burnt scenarios. For the pre-fire (baseline) scenario, the watershed is calibrated by using the measured discharge and suspended sediment concentration data from the weather station during the time step to estimate post-fire changes at the sub-catchment scale. The total water and sediment yield for the selected sub-catchment in the post-fire scenario with the highest spatial distribution of forest fire, due to the excessive surface runoff (an increase of 14.5%) increased significantly, resulted in 6.5 times increase in sediment yield. The results obtained from the study indicate a significant increase in sediment transport into the stream in the post-fire scenario. A large volume of soil losses occurred during the time step. In contrast, due to removing trees and vegetation from the ground, less evapotranspiration and infiltration occurred in selected sub-catchment areas after forest fires. In terms of watershed management, understanding the consequences of forest fires on hydrological services will be an effective method for sediment budget control. Therefore, applying the rainfall-runoff and erosion models for the watershed with developing plausible forest fire scenarios can be a productive method to deal with the threats and hydrological risks such as soil erosion and sediment transfer to the downstream environment.

Spatial and temporal variations of hydrodynamics and sediment dynamics in Indus River Estuary,Pakistan

&lt;p&gt;Field investigations were conducted to study the seasonal variation of hydrodynamics and sediment transport in Indus River Estuary (IRE), Pakistan. The data of water levels, currents, salinity, and suspended sediment concentration (SSC) were collected hourly covering both wet and dry seasons. Tidal amplitudes were higher near the mouth than those at the middle and upper estuary. The ebb phase lasted longer than that of the flood during the wet season. The asymmetric tidal pattern with higher ebb velocity was observed during the wet season. A slight difference in current velocity was found during the dry season. The flood currents were higher at middle estuary than those in wet season. During the wet season, salinity variation within a tidal cycle slightly increased from the upper estuary to the mouth. Salinity was substantially higher during the dry season than the wet season at all three stations, with the absence of the flood-ebb variation, showing a strong saltwater intrusion. The SSC data revealed that the sediments were mainly brought into the estuary by freshwater discharge during the wet season. Sediment re-suspension process persists during the dry season, due to the tidal currents. A stronger saltwater intrusion occurred in the dry season due to weak river discharge. An estuarine turbidity maximum zone was formed near station-2 due to the combined effects of tides, river discharge and saltwater intrusion. Overall, field observations have shown a significant spatial and temporal variation in flood/ebb and wet/dry seasons for hydrodynamics and sediment transport in IRE.&lt;/p&gt;&#x0D;

Real-time forecasting of suspended sediment concentrations in reservoirs by the optimal integration of multiple machine learning techniques

Study regionShihmen Reservoir is ranked the second largest designed storage capacity in Taiwan. Study focusThe accurate forecasting of suspended sediment concentrations (SSCs) during typhoons is critical for effective reservoir management. This paper proposes a two-step switched machine learning (ML)-based approach for constructing an effective model to forecast reservoir SSCs. Different ML algorithms are adopted in the first ML step to build multiple ML-based SSC forecasting models, including multilayer perceptrons, random forest, support vector machines (SVMs), deep neural networks, recurrent neural networks, long short-term memory (LSTM) networks, and gated recurrent units. To compensate for a deficiency in measured SSC data, historical typhoons are modeled using the well-validated SRH-2D numerical model. The second step develops a switched forecasting strategy to optimally integrate forecasts from multiple ML-based models to provide more accurate calculations. New hydrological insightsThe SSC forecasts obtained from the SVM and LSTM are confirmed to be superior to those from other ML-based models. The proposed model (optimally integrated from multiple ML-based models) outperforms the others, particularly when forecasting 1 and 3 h ahead. The proposed model improves the accuracy of SCC forecasts and can be used for sedimentation management in reservoirs during typhoons.

Tidal Asymmetry in Ocean-Boundary Flux and In-Estuary Trapping of Suspended Sediment Following Watershed Storms: San Francisco Estuary, California, USA

Suspended-sediment flux at the ocean boundary of the San Francisco Estuary—the Golden Gate—was measured over a tidal cycle following peak watershed runoff from storms to the estuary in two successive years to investigate sediment transport through the estuary. Observations were repeated during low-runoff conditions, for a total of three field campaigns. Boat-based measurements of velocity and acoustic backscatter were used to calculate water and suspended-sediment flux at a location 1 km landward of the Golden Gate. Suspended-sediment concentration (SSC) and salinity data from up-estuary sensors were used to track watershed-sourced sediment plumes through the estuary. Estimates of suspended-sediment load from the watershed and net suspended-sediment flux for one up-estuary subembayment were used to infer in-estuary trapping of sediment. For both post-storm field campaigns, observations at the ocean boundary were conducted on the receding limb of the watershed hydrograph. At the ocean boundary, peak instantaneous suspended-sediment flux was tidally asymmetric and was greater on flood tides than on ebb tides for all three field campaigns, due to higher average SSC in the cross-section on flood tides. Shear-induced sediment resuspension was greater on flood tides and suggests the presence of an erodible pool outside the estuary. The storms in 2016 led to less export of discharge and sediment from the watershed and greater sediment trapping within one up-estuary subembayment compared to that observed in 2017. Results suggest that substantial trapping of watershed sediments occurred during both storm events, likely due to the formation of estuarine turbidity maxima (ETM) at different locations in the estuary. ETM locations were forced nearer the ocean boundary in 2017. Additional measurements and modeling are required to quantify the long-term sediment flux at the Golden Gate.

Effectiveness of heuristic approach for daily sediment flow prediction of Koyna river basin

The aim of this study was to test the applicability of heuristic approach for daily suspended sediment concentration (SSC) prediction of Koyna river basin situated in western Maharashtra region of India. Daily rainfall, runoff and SSC data were used for development of different models. Heuristic based models like artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS), statistical model like multiple linear regressions (MLR) and traditional sediment rating curve (SRC) models were developed for SSC prediction. In order to avoid time consuming and tedious trial and error method by varying inputs, Gamma test was applied to select best inputs for development of different SSC prediction models. 39 ANN models were developed using tansig, logsig and purelin transfer function. 48 ANFIS models were developed using subtractive clustering method of FIS generation. The best model was selected on the basis performance criteria such as higher correlation coefficient (r) and coefficient of determination (R2). It was found that ANN (6-7-1) model with purelin transfer function outperformed all other models with r and R2 values of 0.79 and 0.62, respectively for daily SSC prediction. The traditional SRC model performed worst and could not able to catch the overall shape of observed SSC time series. The coefficient of determination (R2) was increased from 0.42 to 0.62 using heuristic approach than traditional SRC method. It was found that the heuristic approach could be successfully applied for cumulative SSC load estimation which is essential in reservoir operations and managements. It proves the applicability of heuristic approach in hydrologic modelling for better watershed planning and management.

NUMERICAL MODELLING OF SUSPENDED SEDIMENT DYNAMICS IN THE MEKONG DELTA

Delft3D Flexible Mesh (DFM) was used in 2D to compute hydrodynamics and sediment transport in the Mekong Delta. DFM is a process-based model which is solves the two- and three-dimensional shallow equations, based on the finite volume method (Kernkamp et al., 2011).The computational grid covers the entire Mekong Delta, from Kratie, Cambodia to East Sea shelf. It consists of a multi-dimensional grid which includes 1D and 2D combinations. The primary and secondary canals are represented in 1D networks while 2D cells are used for the Mekong River mainstreams, floodplains and shelf. The hydrodynamics results was calibrated and validated by (Thanh et al., 2019). The sediment model was calibrated against the measured data of suspended sediment concentration and fluxes during water year 2011.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/qnKtpFcrMWU

Field methods of a near-bed suspended sediment experiment in the Yangtze River, China

Using experimental data of near-bed suspended sediment concentrations at five typical hydrometric stations of the Three Gorges Reservoir at the early reserving stage, the differences were investigated between the common method and improved method during flood seasons and non-flood seasons. The impact of taking measurements below 0.2 times the water depth on the results was discussed. The results show that the average discharges and velocities at each station calculated by the common method were slightly larger than those calculated by the improved method. Regarding the suspended sediment concentration at each station, the errors in the reservoir and downstream channels in dynamic equilibrium state were small, and the largest errors occurred where the river bed was strongly scoured in the downstream reach below the large dam. There was no significant relationship between water discharge and flow velocity, and the missed measurement phenomenon also occurred. The sediment discharge error was affected by the suspended sediment concentration, implying that errors usually occurred in channels with serious erosion during flood seasons. The correction coefficients (R2) of sediment discharge at each station were given during the experiment, which showed that the sediment discharges at the hydrometric stations where a large amount of sediment transport occurred near the river bottom, needed to be modified. Furthermore, the test methods proposed in this study were applied to calculate the sediment discharges of three rivers, and the results indicate that this method can narrow the gap between bathymetric comparisons and sediment load measurements.