Suspended Sediment Concentration Research Articles

Relationship Between Aquatic Factors and Sulfide and Ferrous Iron in Black Bloom in Lakes: A Case Study of a Eutrophic Lake in Eastern China

Black bloom is a very serious water pollution phenomenon in eutrophic lakes, with Fe(II) and S(−II) being the key limiting factors for this problem. In this paper, three different machine learning methods, namely, Random Forest (RF), Gaussian Mixture Model (GMM), and Bayesian Network (BN), were used to explore the complex interactions among Fe(II), S(−II), and other aquatic factors in the estuary of Chaohu Lake to better characterize and monitor water degradation by black bloom. The results of RF showed that total nitrogen (TN), ammonia, total phosphorous (TP), suspended sediment concentration (SSC), and oxidation–reduction potential (ORP), which were chosen from 11 factors, had the most important relationships with Fe(II) and S(−II). The 69 sampling sites were divided in three groups identified as worst, worse, and bad according to the observed values of seven factors using the GMM. Then, the BN model was applied to three observation groups. The results showed that the structures of the interaction networks were different between the groups. S(−II) controlled only SSC production in the bad and worse group sites, while SSC was determined by both S(−II) and Fe(II) in the worst group. Ammonia and TN exhibited the most direct importance for S(−II) and Fe(II) production in all observation groups. According to the indications from the BNs, potential management strategies for different water pollution conditions were developed. Finally, the threshold values of Fe(II), S(−II), TP, ammonia, TN, SSC, and ORP, which were 0.80 mg/L, 0.04 mg/L, 0.45 mg/L, 3.44 mg/L, 4.15 mg/L, 55 mg/L, and 135 mv, respectively, were determined on the basis of the BN models. These values will be helpful to develop accurate strategies of oxygenation to quickly eliminate black bloom in the lake.

Impacts of changing weather patterns on the dynamics of water pollutants in agricultural catchments: Insights from 11-year high temporal resolution data analysis

Widespread and long-term shifts in weather patterns are contributing to further degradation of surface water quality. This challenge caused by the increasing frequency of extreme weather events requires appropriate adaptation of current mitigation strategies. But to confirm the need to redesign such strategies, an understanding of the impacts of increasing weather extremes on pollutant losses in different catchment types is required. With this in view, this study investigated the impact of changing weather patterns on the inter-seasonal and inter-annual dynamics of nutrient losses in six agricultural catchments in Ireland over 11 years. The high temporal resolution data (10-min) from these intensively managed catchments represented different characteristics and management practices. Mann-Kendall Trend Analysis and Generalised Additive Models were used to study nutrient concentration trends, and to investigate the significance of water discharge, precipitation, potential evapotranspiration, soil moisture deficit, air temperature, and soil temperature on the losses of nutrients, respectively. The analysis of historical data revealed changes in the trends of daily average nitrate (NO3-N), phosphorus (P), and suspended sediment (SS) concentrations in association with significant increasing trends in air temperature, soil temperature, and precipitation across the same month over 11 years of monitoring. While discharge was significantly contributing to the concentrations of NO3-N, P, and SS across different catchments, air and soil temperature were significantly correlated to NO3-N losses, and precipitation was the major contributor to regulating P (total P and total reactive P) concentrations. In short, air temperature, soil temperature, soil moisture deficit, and precipitation were the main climatic drivers regulating the nutrient concentrations while the soil chemistry and drainage status were the non-climatically related drivers. The results revealed that the extent of the impact of climatic drivers depends on catchment characteristics. Therefore, expanding the application of this type of study would facilitate better understanding of current and future challenges to water management and provision of climate-resilient mitigation strategies for different catchment typologies.

Hydrochemical characterization and pCO2 dynamics in the surface waters of Himalayan River: A case study of river Alaknanda.

Chemical weathering processes are becoming increasingly important in studies on carbon cycling because they are responsible for increased solute fluxes in the proglacial zone, can effectively sequester atmospheric CO2 and raise carbon budgets for lateral transport via rivers. Here, we examined the hydrochemical and hydrogeochemical processes, solute sources and factors controlling riverine pCO2 of the Alaknanda River and its tributaries for three sampling seasons, viz. pre-monsoon (May 2021), post-monsoon (October 2021) and winter (January 2022). The surface water is enriched with Ca2+ and Mg2+ as the dominant cations, while HCO3- and SO42- were the major anions. Gibbs's plot confirmed rock weathering as the leading mechanism in controlling the hydrochemistry of the basin. The chemical composition of river water was mainly regulated by the weathering of carbonate end members: dolomite, limestone and feldspar along with small inputs from silicate weathering. The mean pCO2 values in the mainstream (1702.7 µatm), Pindar (2267.9 µatm) and Mandakini (1136.1 µatm) revealed the streams were oversaturated with CO2 having a higher rate of exporting excess CO2 gas to the atmosphere. The study showed the persistence of high pCO2 closed system characteristics associated with increased suspended sediment concentration resulting from carbonate weathering, dominance of HCO3- over SO42- and thereby results in high values of C ratio. Principal component analysis of the water chemistry suggests that weathering contributes about 41%, while humans contribute about 13% of the ionic load to the river. This study is one of its kind to understand the system characteristics of Alaknanda River water.

Inferring sediment-discharge event types in an Alpine catchment from sub-daily time series

Abstract. Fluvial sediment dynamics in mountain rivers are changing rapidly in a degrading cryosphere, raising the potential for erosive rainfall and runoff and detrimental effects on downstream areas. Hence, we need to understand better what characterises and drives episodic pulses of water and suspended solids in rivers. Here, we infer different types of such sediment-discharge events from 959 automatically detected events based on 16 metrics derived from 15 min time series of streamflow and suspended sediment concentrations from Vent–Rofental in the high Ötztal Alps, Austria. We use principal component analysis to extract uncorrelated event characteristics and cluster event types with a Gaussian mixture model. We interpret the thus inferred event types with catchment metrics describing antecedent conditions, hydrometeorological forcing, and fraction of catchment area with freezing temperatures and snow cover. We find event magnitude, hysteresis, and event shape complexity to be the main factors characterising the overall event regime. The most important characteristics distinguishing the event types are suspended sediment and streamflow magnitude and complexity of the hydro- and sedigraphs. Sediment-discharge hysteresis is less relevant for discerning event types. We derive four event types that we attribute to (1) compound rainfall–melt extremes, (2) glacier and seasonal snowmelt, (3) freeze–thaw-modulated snowmelt and precipitation events, and (4) late-season glacier melt. Glacier and snowmelt events driven by warm conditions and high insolation were the most frequent and contributed some 40 % to annual suspended sediment yield on average; compound rainfall–melt extremes were the rarest but contributed the second-highest proportion (26 %). Our approach represents a reproducible method for objectively estimating the variety of event-scale suspended sediment transport conditions in mountain rivers, which can provide insights into the contribution of different drivers to annual sediment yields in current and future regimes. Our findings highlight the importance of both meltwater and rainfall–runoff as drivers of high-magnitude suspended sediment fluxes in mountain rivers.

Deglaciation in the subtropical Andes has led to a peak in sediment delivery

Glaciers are thinning and retreating as climate warms, thus eroding less of the Earth’s surface. However, other hydrological factors in glacierized catchments are likely producing a transient increase in sediment delivery, resulting in ‘peak sediment’. Estimating the trajectory of the peak sediment is ecologically and socially important but scientifically challenging because of the delayed and non-linear response of glacier sediment export to climate forcing. This study used time series of suspended sediment concentration starting in the 1960s from 11 Andean rivers at subtropical latitudes to analyse past changes in sediment export and infer its future behaviour. The recent decade has experienced anomalously high sediment concentration in most glacierized catchments, but the 1970s experienced even higher values. Decadal variations in the relationship between sediment concentration and ice melt suggest that the magnitude of the current decade was lower due to reduced glacial sediment rather than other factors. Combining this result with the fact that glacial runoff is decreasing, it is inferred that, for most of the glacierized catchments, the peak sediment generated by the anthropogenic deglaciation started two centuries ago has already passed its maximum.

Implications of suspended sediment in the migration of nutrients at the water-sediment interface in retention reservoirs

The significance of suspended sediment in the context of nutrient cycling and distribution in reservoirs is rarely reported in the scientific literature. What’s more, suspended sediment (SS) have so far not been taken into account as a potential factor amplifying the degrading effects of nutrients on the functioning of reservoirs. In the experiment described here, the variability of SS concentrations and the content of total nitrogen (TN), total phosphorus (TP), total organic carbon (TOC) and organic matter (OM) were investigated to determine the potential and determinants of SS in the process of migration of these substances at the water-sediment interface in retention reservoirs. The results showed that SS significantly manipulate the distribution of values of total phosphorus and total organic carbon contained in bottom sediment. It was confirmed that the circulation and distribution of selected nutrients in reservoirs is closely related to suspended sediment. Thus, it was proven that SS significantly affect the quality of deposited sediment. Finally, it was concluded that suspended sediment in the water of reservoirs forms a kind of micro-ecosystem, in which it plays a hitherto undiscovered role of a catenary (hub) consolidating a number of phenomena and processes occurring between individual components in the water-bottom sediment system.

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.

A smart, multi-configuration, and low-cost system for water turbidity monitoring

Measuring the amount of suspended sediment in rivers is important for a better understanding of phenomena like soil erosion or floods. Since such phenomena are not spatially homogeneous, a distributed measurement approach is required to obtain fine-grained and realistic models. We designed and implemented a low-cost, flexible, and smart suspended sediment concentration monitor. The system only uses components that are easy to find and assemble. This, together with the reduced costs, enables the use of multiple instances for distributed monitoring. The system can operate according to different configurations, fixed or mobile, and using a variety of connection technologies, to possibly cover the various necessities that arise from the diverse installation sites. Each measuring unit automatically retrieves its operational parameters, easing the configuration of a possibly large distributed measurement system.

Numerical modeling of graded sediment transport with limited bed material supply – A case study in the Middle Yangtze River

Suspended sediment concentration in the Middle Yangtze River (MYR) has reduced sharply below the Three Gorges Dam since 2003, and led to significant channel degradation and riverbed coarsening. However, the complex interaction between riverbed coarsening and sediment transport is essential for channel evolution processes but is poorly understood. This paper presents a one-dimensional model for simulating graded sediment transport when the bed material supply is limited. The model takes account of the effect of bed material composition (BMC) and threshold probability on graded sediment transport, and thus improve the accuracy of recovery coefficient. The modeling results of graded sediment concentrations was calibrated and then satisfactorily verified using field observations in the JingJiang Reach from 2015 to 2016. The results showed bed material composition affect the simulated fine, medium, and coarse sediment concentrations, and the improvements of normalized errors are 17.6%, 45.9%, and 330.7%, respectively. With the BMC effect considered, the recovery factor of fine and medium were far less than coarse sediment in the MYR. In addition, the recovery ratios of medium and coarse sediment concentrations along the MYR were improved by 88.6%-265.4% and 75.1%-105.9% respectively, owing to the bed material supply after the TGD operation; however, there was no significant effect on fine sediment, with a low recovery ratio of 8.3%-8.6%. Therefore, the effect of bed material composition on graded sediment transport and channel evolution needs to be considered for higher simulation accuracy in the MYR.

Variation of suspended-sediment caused by tidal asymmetry and wave effects

Suspended sediment plays an important role in coastal topography evolution and ecological environment change. To obtain a clear picture of the underlying mechanisms, we studied the response of suspended sediment dynamics to tidal current and wave-current interactions using the wave-current-sediment model of SCHISM. The results revealed evident tidal asymmetry in the study area, and showed that the suspended sediment concentration (SSC) markedly changes within a tidal cycle. We also disassembled the wave–current interactions to determine the contribution of each physical mechanism of the wave and hydrodynamic models. Regarding the importance of various effects of wave-current interactions on SSC, the wave-induced bottom shear stress and wave-induced radiation stress should be considered. The importance of advection in horizontal space is comparable to that of wave-induced bottom shear stress and wave-induced radiation stress, and is greater than that of the other types of wave energy advection. This study successfully explained all the mechanisms that influence the variation of SSC to the southwest of Hainan Island, which is helpful for coastal management and could provide a reference for other coastal areas.

Oceanographic monitoring in Hornsund fjord, Svalbard

Abstract. Several climate-driven processes take place in the Arctic fjords. These include ice–ocean interactions, biodiversity and ocean circulation pattern changes, and coastal erosion phenomena. Conducting long-term oceanographic monitoring in the Arctic fjords is, therefore, essential for better understanding and predicting global environmental shifts. Here we address this issue by introducing a new hydrographic dataset from Hornsund, a fjord located in the southwestern part of the Svalbard archipelago. Hydrographic properties have been monitored with vertical temperature, salinity and depth profiles in several locations across the Hornsund fjord from 2015 to 2023. From 2016 onward, dissolved oxygen and turbidity data are available for the majority of casts. The dataset contributes to the so far infrequent observations, especially in spring and autumn, and extends the observations, typically concentrated in the central fjord, to the areas adjacent to the tidewater glaciers. Because sediment discharge from glaciers and land is an inseparable part of the glacier–ocean interactions, the suspended sediment concentration in the water column and the daily sedimentation rate adjacent to the tidewater glaciers are monitored with regular water sampling and bottom-moored sediment traps. Here we present the planning and execution of the monitoring campaign from the collection of the data to the postprocessing methods. All datasets are publicly available in the repositories referred to in the “Data availability” section of this paper.

Analysis of fine-grained sediment dynamics from field observations with a vector autoregressive model

Empirical models and process-based theoretical or numerical models are valuable tools for analyzing sediment dynamics by reproducing the suspended sediment concentration (SSC) observations, but they are either limited by simplified assumptions or computationally complex. Some data-driven models have been developed to predict SSC but are still weak in explaining the causes of its changes. A field observation of silty sediment dynamics was performed in the Yellow River Delta, China. Then, a vector autoregressive (VAR) model is employed to analyze and predict the SSC variations. Using the impulse response function, the VAR model quantifies the transient and cumulative responses of the SSC to storm and current shocks (i.e., the impulse input), which reveals the key mechanisms of SSC changes from a new perspective. Results show that the storm effect on SSC in the study area lasts for ca. 85 h, and the SSC peaks at around the 36th hour with a cumulative increase of about 1.3 g/L due to the storm’s cumulative effect. Quantitative analysis reveals that waves contribute 73.78% to the SSC, while tidal currents contribute 26.22%. Fine SSC is significantly impacted by horizontal advection. A single reciprocal motion of the tidal current affects the SSC for approximately 6.25 h, while the overall duration exceeds 100 h. The proposed model physically reveals that the storm-induced high concentration gradient has been pushed back and forth by the tidal currents, affecting the SSC at the observation site, and the horizontal advection effect lasts for more than 100 h. Moreover, the VAR model achieves high-accuracy interval predictions of SSC for the next 5 h using only historical hydrodynamic data, with a 100% coverage probability of the 95% prediction interval. This paper provides a simple and efficient method for sediment dynamics analysis, which is of great significance for marine environment protection and disaster warning.

Interpreting machine learning models based on SHAP values in predicting suspended sediment concentration

Machine learning (ML) has become a powerful tool for predicting suspended sediment concentration (SSC). Nonetheless, the ability to interpret the physical process is considered the main issue in applying most of ML approaches. In this regard, the current study presents a novel framework involving four standalone ML models (extra trees (ET), random forest (RF), categorical boosting (CatBoost), and extreme gradient boosting (XGBoost)) and their combination with genetic programming (GP). Three metrics (coefficient of correlation (r), root mean square error (RMSE), and Nash–Sutcliffe model-fit efficiency (NSE)) and a more advanced interpretation system SHapley Additive exPlanations (SHAP) are used to assess the performance of these models applied to hydro-climatic datasets for prediction of SSC. The calibration process was based on data from 2016 to 2020, and the validation was done for 2021 data. Further description and application of the framework are provided based on a case study of the Bouregreg watershed. The results revealed that all implemented models are efficient in SSC prediction with NSE, RMSE, and r varying from 0.53 to 0.86, 1.20 to 2.55 g/L, and 0.83 to 0.91 g/L respectively. Box plot diagrams confirm the enhanced performance of these combined models, and the best-performing ones for the four hydrological stations being the combined RF+GP model at the Aguibat Ziar station, the combined XGBoost+GP model at the Ain Loudah station, the CatBoost model at the Ras Fathia station, and the RF model at the Sidi Med Cherif station. The interpretability results showed that flow (Q) and seasonality (S) are the features most impacting SSC. These outcomes indicate that the applied models can extract accurate and detailed information from the interactions between the hydroclimatic factors and the generation of sediment by erosion (output). ML approaches illustrated the good reliability and transparency of the models developed for predicting SSC in a semi-arid setting, offered new perspectives for reducing ML models' "black box" character, and provided a useful source of information for assessing the consequences of SSC on water quality. The SHAP system and exploring other interpretable techniques are recommended to provide further information in future research. In addition, incorporating additional input data could enhance SSC predictions and deepen understanding of sediment transport dynamics.

Modeling the transport and mixing of suspended sediment in ecological flows with submerged vegetation: A random displacement model-based analysis

Aquatic vegetation in rivers influences the flow structure, impacting the sediment transport in the river and further changing the ecosystem and geomorphologic evolution of the river. In this paper, an improved random displacement model (RDM) is proposed to investigate the concentration of suspended sediment (CSS) in flows with flexible submerged vegetation. Considering the effect of sediment resuspension on sediment transport, a probability model of sediment resuspension is embedded into the RDM so that the simulation process is more consistent with the natural cases. For the streamwise development of flow with flexible submerged vegetation, the flow is divided into a flow adjustment region and a fully developed region in the longitudinal direction. The vertical distributions of the flow velocity and turbulence diffusion coefficient were analyzed in these two regions, and they were incorporated into the RDM to simulate the along-flow development of the CSS. The simulated concentrations were compared with the experimental data. The mean relative errors (MREs) were below 15%, the root mean square errors (RMSEs) were below 0.20, and the Nash–Sutcliffe efficiencies (NSEs) ranged from 0.71 to 0.99, indicating that the improved RDM is plausible and reliable. In addition, the along-flow distribution of the sediment transport rate (STR) was analyzed. The rate exhibited a decreasing trend during the flow adjustment region and tended to stabilize during the fully developed region. This study provides a new way of thinking for research on sediment transport in rivers with aquatic vegetation, which is of great significance for achieving the sustainable development of river ecosystems and the optimal design of river channels.

Conditional Effects of Tides and Waves on Sediment Supply to Salt Marshes

AbstractThe survival of salt marshes, especially facing future sea‐level rise, requires sediment supply. Sediment can be supplied to salt marshes via two routes: through marsh creeks and over marsh edges. However, the conditions of tides and waves that facilitate sediment import through these two routes remain unclear. To understand when and how sediment is imported into salt marshes, 2‐month measurements were conducted to monitor tides, waves, and suspended sediment concentration (SSC) in Paulina Saltmarsh, a meso‐macrotidal system. The results show that the marsh creek tends to import sediment during neap tides with waves. A tidal cycle with a small tidal range result in weaker flow in the marsh creek during ebb tides, reducing the export of sediment. Waves enhance sediment supply to the marsh creek by eroding mudflats. However, strong waves can directly resuspend sediment in marsh creeks during spring tides when the water level is above the marsh canopy, enhancing sediment export through creeks. Net sediment import over marsh edges requires the opposite tidal and wave conditions: spring tides with weak waves. Spring tides provide stronger hydrodynamics, facilitating sediment import over the marsh edge. Increased SSC during the ebb phase can occur with strong waves over the marsh edge, resulting in net sediment export. Therefore, the net import or export of sediment, through the creek and over the marsh edge, depends on the combination of tidal and wave conditions. These conditions can vary between estuaries and even individual marshes. Understanding these conditions is crucial for better management of salt marshes.

Factors Controlling Mud Floc Settling Velocity in a Highly Turbid Macrotidal Fluvial‐Estuarine System

AbstractThis study assesses the settling dynamics of suspended sediments along the hyper‐turbid Gironde Garonne fluvial‐estuarine system, with an innovative optical SCAF instrument (System of Characterization of Aggregates and Flocs). Two fields campaigns were carried out to determine the settling velocity and properties of suspended sediments during a semi‐diurnal tidal cycle, as well as hydrodynamic conditions and water properties. The two sampling stations were representative of two regions: a tidal river dominated by fresh water and an estuary affected by salty or brackish waters. A high spatial variability of the settling velocity was observed along the fluvial‐estuarine system and vertically along the water column. Settling velocities ranged from 0.02 to 0.4 mm/s. This study confirms that in hyper‐turbid systems, the suspended sediment concentration (SSC) is predominantly driving the settling dynamics of suspended sediment. Threshold concentrations have been defined for the flocculation and hindered regimes where the settling velocity may vary by one order of magnitude. Although in natural environments it is difficult to distinguish between the effects of SSC and turbulence (as they are correlated), in the Gironde‐Garonne system the turbulent shear G seems to affect the settling of suspended sediment to a lower extent. Settling velocity variations cannot be directly correlated to salinity or organic matter content. Despite differences in hydrodynamic and environmental conditions in fluvial and estuarine regions, a common prediction law has been found to estimate settling velocity of suspended sediment as a function of suspended sediment concentration.

Water Column Nitrogen Removal During Storms in a Low‐Order Watershed

AbstractWater column removal in streams is a nitrogen (N) cycling pathway that has been historically overlooked. Studies filling this knowledge gap have focused on the role of water column N removal in mid‐to‐large‐order rivers with consistently high suspended sediment concentrations. However, smaller streams may provide comparable suspended sediment concentrations during and after storm events, creating favorable conditions for water column N removal. To assess the presence, magnitude, and control of water column N removal during storms in low‐order watersheds, we measured water column denitrification and heterotrophic assimilatory N uptake rates at three locations in a Mid‐Atlantic watershed during five storm events of different magnitude, sediment loads, and nutrient availability. We found large variations in water column denitrification (0–5.56 mg N g−1 d−1) and assimilatory uptake (0.003–1.67 mg N g−1 d−1). Higher rates of N removal occurred during flow recession, with a correlation between suspended sediment organic matter content and denitrification. On average, denitrification rates in the water column were higher when flashy responses to storm events occurred. In contrast to denitrification, water column N removal rates (as both denitrification and heterotrophic assimilation) during storm events were comparable to those measured at baseflow in larger rivers. However, water column denitrification could only account for less than 10% of potential reach‐scale N removal during most of the storm events. Our findings provide insight into the ecological relevance of small stream water columns and suggest that more research is needed to understand the magnitude of stream water column processing on watershed‐scale N removal.

The impact of a storm on the microtidal flat in the Yellow River Delta

Strong hydrodynamic forces generated by storms are key in shaping coastal tidal flats. Most tidal flats achieve equilibrium by adapting to hydrodynamic conditions and sediment inputs. However, high-energy wave activity during storms disrupts this equilibrium, causing rapid and significant changes, particularly in tidal flats, especially in microtidal flats, which are characterized by low tidal ranges. In this study, we conducted an 11-d field campaign on a microtidal flat in the Yellow River Delta (YRD), capturing data during both stormy and calm weather conditions. We measured tidal currents, wave activity, suspended sediment concentrations and sediment grain sizes. The results demonstrated that the tidal flat maintained equilibrium under calm conditions, with minimal fluctuations in bed level (within ±2 mm). Contrastingly, severe erosion and sediment removal during the storm significantly altered the equilibrium of the area. The storm-induced high shear stresses, ranging from 1.02 to 1.48 , along with alongshore sediment transport, resulted in an elevation change of -10 mm. Furthermore, the subsequent bed level recovery was minimal and insufficient to offset the erosion. Compared to that of the mesotidal and macrotidal flats, post-storm recovery on microtidal flats was limited due to shorter inundation periods and weaker hydrodynamic forces. Therefore, frequent storms may lead to continuous shoreline retreat on microtidal coasts. Conclusively, the present findings underscore the significant impact of storm-induced erosion on the evolutionary processes of microtidal flats and suggest that greater attention should be given to protecting these areas during storms in the Yellow River Delta. The insights can guide the development of more effective coastal protection strategies, highlighting the need for enhanced measures to mitigate erosion and promote resilience in microtidal regions.

Sediment Dynamics in the Energetic Nearshore Zone: Acoustic Remote Sensing and Model Validation

AbstractAcoustic backscatter data were collected in the shallow nearshore environment under breaking and non‐breaking waves, using a multi‐frequency sonar at 0.5, 1.0, and 2.0 MHz. The data are used to develop and test an acoustic inverse model for measuring suspended sediment concentration (SSC) in the presence of bubbles generated by breaking waves. The model leverages the contrasting frequency dependence of acoustic scattering by bubbles and sand, to simultaneously estimate SSC and bubble void fraction. Validation against in situ sediment measurements shows the acoustic technique can recover sediment concentration with good accuracy in both breaking and non‐breaking waves, unlike existing algorithms which only perform well in non‐breaking waves. Finally, data from the experiment are used to validate existing theories for suspended sediment dynamics under breaking waves, for which few previous data sets exist.

Influence of the Suspended Sediment Concentration on the Calculation of the Vertical Distribution of Streamwise Velocity

Influence of the Suspended Sediment Concentration on the Calculation of the Vertical Distribution of Streamwise Velocity