Suspended Sediment Model Research Articles

Incorporating memory effect into a fractional stochastic diffusion particle tracking model for suspended sediment using Malliavin-Calculus-based fractional Brownian Motion

This study aims to develop a Fractional Stochastic Diffusion Particle Tracking Model (FSDPTM) to illustrate suspended sediment’s long-term dependence (LTD) trajectories immersed in fully developed turbulent flow. Carried by eddies in the open channel, individual suspended sediment behavior exhibits dependence on its past increments. The Fractional Brownian Motion (FBM) is incorporated into the FSDPTM to account for the randomness of turbulent flow and to include the time-dependent increments as a memory effect. Additionally, to enhance the capacity for differentiating FBM, this study introduces Malliavin Calculus, the stochastic calculus of variation, to construct the square -differentiable FBM. For the numerical realizations of square differentiable FBM, the integration of fractional Gaussian white noise and Wiener–Ito Chaos expansion with the Hermite sequence is employed. The FSDPTM offers probabilistic LTD trajectories as solutions to the Ito-type Langevin equation. It also provides particle velocity, acceleration, and ensemble statistics, collectively demonstrating the application of FBM to sediment transport modeling. In conclusion, the key feature of the FSDPTM is its ability to translate LTD derived from FBM into the trajectory of suspended sediment particles in fully developed turbulent flow. Additionally, it expands the solutions from non-differentiable to square-differentiable stochastic processes.

Modeling sediment concentrations and loads for two small agricultural watersheds in Prince-Edward-Island (Canada): present conditions and a future scenario

The degradation of soils and its detrimental consequences on aquatic environments is an important research topic in agricultural regions such as Prince Edward Island (PEI, Canada). Enhanced information related to suspended sediments in watercourses can serve as an effective decision-making tool in agricultural land management. This study aims to compare flow, suspended sediment concentrations (SSC), and loads using the Soil and Water Assessment Tool (SWAT) in two watersheds in Prince Edward Island (PEI). The final investigations will focus on the potential variations in hydrological and sedimentary values in the future using a relatively pessimistic climate change scenario. Finally, the projected sediment concentrations and loads will be analyzed, considering their potential impacts on ecosystems. Water level and turbidity were recorded using two water level loggers and two optical backscatter sensors (OBS) deployed in the Tuplin Creek and Spring Valley watersheds. These instruments continuously recorded suspended sediments and flow data from June 2021 to September 2022. The data were used to manually calibrate the hydrological and suspended sediment models. The understanding of sediment loads and the benefits of proposed changes to agricultural practices can be tested with the SWAT model, as it incorporates a land use index that varies spatially and temporally. Calibration and validation of both the hydrological and sediment models were satisfactory, with Kling-Gupta Efficiency coefficients varying between 0.51 and 0.73 and Nash-Sutcliffe coefficients varying between 0.61 and 0.73 respectively, indicating successful simulation of both variables in an agricultural context in spite of relatively short calibration and validation periods. Under the selected climate change scenario (RCP 8.5), daily flows and suspended sediment concentrations were simulated until 2,100, showing a slight increase in the average suspended sediment concentration (CSS). For Tuplin Creek, extremely high sediment peaks (>1,500 mg/L) could become significantly more frequent, potentially causing more frequent and severe ecosystem disturbances according to the simulations.

Monitoring of chlorophyll-a and suspended sediment concentrations in optically complex inland rivers using multisource remote sensing measurements

In recent decades, phytoplankton proliferation and sediment input to rivers (especially urban rivers) have become more dramatic under the compound pressure of climate change and human activities. Given the generally narrow width of rivers and current high spatial resolution satellites, which are limited by band settings, bandwidth, and the signal-to-noise ratio, UAVs with their exceptional spatiotemporal resolution can be used as a useful tool for river environmental monitoring and inversion uncertainty assessment. In this study, UAV-based hyperspectral (X20P) and multispectral (P4M) images, along with Sentinel-2 MultiSpectral Instrument (MSI), Landsat-8 Operational Land Imager (OLI) and Landsat-9 OLI2 data, were used to assess the uncertainty in retrieving chlorophyll-a (Chla) and suspended sediment (SS) concentrations in rivers. Chla and SS models based on UAV and satellite data were constructed using stepwise multiple regression and typical Chla and SS retrieval algorithms, respectively, and the performance of the models was the focus of our research. The results demonstrated that in the Chla concentration inversion, each sensor performed as follows: X20P > P4M > Landsat9 OLI2 > Sentinel-2 MSI > Landsat8 OLI, and the performance in the SS concentration inversion was as follows: X20P > Sentinel-2 MSI > P4M > Landsat9 OLI2 > Landsat8 OLI. In addition, the uncertainty of high spatial resolution satellite retrievals was analyzed with the assistance of the UAV-based model. Results showed that narrow bandwidths and finely tuned band settings are more essential for the Chla inversion. The typical Chla retrieval algorithm, NDCI, is only effective in certain bands (band 1 from 684 to 724 nm and band 2 from 660 to 680 nm). It is also noted that Landsat8 and Landsat9 lack some key band settings (e.g., the red-edge band of 700–710 nm), severely limiting practical application in relation to Chla. However, specific variances in different sensor bands have a relatively small impact on SS inversion, for example, the correlation between SS and the R/B (a typical SS retrieval algorithm) constructed by each sensor ranged from 0.68 to 0.77. Chla monitoring, on the other hand, necessitates a higher spatial resolution than SS monitoring. The accuracy decreased markedly when UAV images were resampled to 10 m and 30 m spatial resolution. However, it is not as crucial for the SS inversion, images with the original spatial resolution (RMSE<30cm = 6.28 mg/L) were resampled to 10 m resolution (RMSE10m = 5.85 mg/L) and 30 m resolution (RMSE30m = 4.08 mg/L) while using P4M for SS inversion, and the accuracy increased. Our results demonstrated and highlighted various options for future monitoring of Chla and SS, while exploiting the synergy between UAVs and satellites to achieve more precise observations at greater spatial and temporal scales, which will benefit aquatic environment management and protection.

A new large-scale suspended sediment model and its application over the United States

Abstract. Suspended sediment plays a vital role in the regional and global cycling of carbon and nutrients by carrying carbon and nutrients from headwaters into lowland rivers and the oceans. Sediment transport through river systems is often fundamentally modified by human activities such as reservoir management. However, a physically based representation of sediment transport is still missing in most existing Earth system models (ESMs), which are essential tools for modeling and predicting Earth system changes. Here, we introduce a multi-process river sediment module for ESMs, which includes (1) hillslope soil erosion and sediment discharge into streams, (2) sediment transport processes through river networks, (3) reservoir operation based on the inflows from upstream areas and water demand from downstream areas, and (4) sediment trapping by reservoirs. All model parameters are estimated a priori without calibration. We apply this new sediment modeling framework to the contiguous United States and validate it against historical observations of monthly streamflow and sediment discharges at 35 river gauges. The model reasonably well captures the long-term balance and seasonal variations of suspended sediment in large river systems. Furthermore, our model results show that suspended sediment discharge in managed rivers is affected more by reservoirs' direct trapping of sediment particles than by their flow regulation. This new sediment module enables future modeling of the transportation and transformation of carbon and nutrients carried by the fine sediment along the river–ocean continuum to close the global carbon and nutrient cycles.

Suspended sediment modelling with hydrological and climate input data

Abstract Measured records of suspended sediment concentrations are vital information to support water management activities. However, these measured time series are often incomplete and, as such, are not suitable for some analyses. This paper sets out the options for modelling suspended sediment concentrations to determine them in periods when measurements were not performed. The Danube River profile in Bratislava was selected as the case study. Regression using least absolute selection and shrinkage operator, support vector regression and deep learning neural network are compared in the paper to solve this task using various data sources. The results obtained show a significant increase in the precision of modelling suspended sediment concentrations over the standard method, which is a rating curve. Several variables were used to establish the suspended sediment concentration, because the same data as in this study may not be available everywhere. In particular, the use of climatic (precipitation and temperature) and hydrological inputs (flows) is assessed in order to promote the more general benefit of work. In the article, the authors propose an original method of modification of input climate data, which significantly increases the accuracy of modelling. The authors demonstrate that when using proposed methodology, the use of climate data, which are usually better available than hydrological data, resulted in a comparable degree of precision to standard modelling based on river flow data.

Numerical Simulation of Ocean Wave Using High-Order Spectral Modeling Techniques: Its Influence on Transport Sediment in Benoa Bay, Bali, Indonesia

Benoa Bay is threatened by sedimentation issue within the bay. It impairs the water mass circulation, influencing scour, mixing, and turbulence as well as sediment transport processes. This study focuses on the wave characteristic and its relation to sediment transport within Benoa Bay. Spectral wave modeling techniques were employed. The equation was discretized based on the condition of winds, tidal, and currents. Total sediment transported was calculated according to the wave model result. Total suspended sediment (TSS) model was simulated which the simulation considers bed load and suspended load transport. Significant wave height (Hs) ranged 0-0.48 m and 0-0.44 m during high tidal condition and low tidal condition respectively. Wave undulation propagates toward the West and Northwest within Bay. The wave period (Ts) ranged 2-6.5 second. Total sediment transport ranged 2828.16 - 86235.66 m3/year. TSS concentration ranged 1-100 mg/L and 1-155 mg/L during high tidal condition and low tidal condition respectively. Those conditions indicate that the sedimentation has been extremely occurred within the bay. The areas around Benoa peninsula, Benoa harbor, and Serangan Island are heavily polluted by suspended sediment. Bottom sediment is stirred by hydraulic jump off wave propagation. The first wave crest induces scour, which its train carries the stirred sediment entering the bay. If ongoing, this condition will exacerbate the existing ecosystem. Benoa Bay development has a big role evoking the level of TSS and turbidity. The more the sedimentation occurs, the more the ecological problem takes place.

Rouse revisited: The bottom boundary condition for suspended sediment profiles

A linearly depth-dependent diffusivity is commonly used to model the vertical distribution of dilute, near-bed, suspended sediment in marine fluid environments, i.e., the Rouse model; this simplified form predicts unfortunately infinite concentration at the bed. That singularity causes problems in linking bed models to suspended sediment models. A common remedy to this problem is to assume a reference concentration and height above the bed, but some studies point to the arbitrariness of that procedure and suggest, instead, the existence of a residual eddy diffusion near the bed, which removes the singularity. In these past studies, the residual diffusion, εo, has been assigned a value based on the Nikuradse roughness height, ks=2.5ds, where ds is the (mean) equivalent sand-grain diameter. We examine this assumption by fitting a residual diffusion model to 14 time-averaged suspended-sediment profiles available in the literature, without assuming the Nikuradse length. This procedure produces εo values from 0.6 to 13cm2s−1, which are much greater than both the (molecular) kinematic viscosity of water and the expected Brownian diffusion coefficient of the sediment grains of the reported sizes. These residual diffusion coefficients indicate mixing scale heights at the bed, εo/κu∗, where κ is von Kármán's constant and u∗ is the shear velocity, are 7.4–56.0× greater than the Nikuradse height, ks. Although defined by only limited data, we also find that the residual diffusion correlates with grain size and the roughness Reynolds number but not with the Rouse parameter, nor with the shear and settling velocities. In addition, the residual diffusion coefficient correlates with van Rijn's roughness scale, again based on the same limited data, suggesting that bedforms influence residual diffusion near the bed.

Modeling of suspended sediment by coupled wave-current model in the Zhujiang (Pearl) River Estuary

A three-dimensional wave-current-sediment coupled numerical model is developed to understand the sediment transport dynamics in the Zhujiang (Pearl) River Estuary (ZRE), China. The model results are in good agreement with observed data, and statistics show good model skill scores. Numerical studies are conducted to assess the scenarios of suspended sediment in the ZRE under the effects of different forcing (river discharges, waves, and winds). The model results indicate that the estuarine gravitational circulation plays an important role in the development of estuarine turbidity maximum in the ZRE, particularly during neap tides. The increased river discharge can result in a seaward sediment transport. The suspended sediment concentration (SSC) in the bottom increases with both wave bottom orbital velocity and wave height. Because of the shallow water depth, the effect of waves on sediment in the west shoal is greater than that in the east channel. The southwesterly wind-induced wave affects the SSC more than those resulting from the northeasterly wind, while the northeasterly wind-driven circulation has a slightly greater influence on the SSC than that of the southwesterly wind. However, a steady southwesterly wind condition favors the increase of the SSC in the Lingding Bay more so than a steady northeasterly wind condition. If the other forcings are same, the averaged SSC under a steady southwesterly wind condition is about 1.1 times that resulting from a steady northeasterly wind.

Three‐dimensional hydrodynamic and sediment transport modeling to test the sediment focusing hypothesis in upland lakes

AbstractPalaeolimnological studies rely on assumptions regarding the distribution and completeness of lake deposits that are not always fully supported by observations. In particular, the assumption that “focusing” of suspended sediments leads to preferential deposition in the deepest part of a lake is not always justified, especially in upland lakes subject to energetic wind forcing. Few studies have investigated the hydrodynamic controls on lake sediment focusing, especially the importance of wind‐driven currents in deep water. We combine a three‐dimensional numerical hydrodynamic and suspended sediment model (FVCOM) with a semi‐empirical wind wave model to investigate the potential mobility of bottom sediments in a small oligotrophic upland lake (Llyn Conwy, north Wales, UK). Exploratory simulations of wave‐ and current‐generated bottom stress and suspended sediment dynamics confirm the expected importance of wave‐generated bottom stresses in shallower waters (&lt; 3 m depth) around the shore. Field survey shows that lake sediments are largely absent from this zone. This is consistent with peripheral wave action as a sediment focusing mechanism. In deeper water, wind‐driven currents become the dominant contributor to bottom stress. Strong wind forcing events drive an energetic circulation with peak bottom stresses that intermittently exceed any realistic erosion threshold over a large proportion of the lake at depths far below those at which waves can be effective. The spatial distribution of lake sediments, and the completeness of the sediment record, is thus determined by a complex interaction between wind‐driven circulation and bathymetry, rather than by bathymetry alone. Although our sediment dynamics simulations are purely exploratory, the results are consisted with survey results that show a patchy distribution of deep‐water accumulation. Some implications of these results for the selection of sediment coring locations and the interpretation of sediment records are considered.

River suspended sediment modelling using the CART model: A comparative study of machine learning techniques

Suspended sediment load (SSL) modelling is an important issue in integrated environmental and water resources management, as sediment affects water quality and aquatic habitats. Although classification and regression tree (CART) algorithms have been applied successfully to ecological and geomorphological modelling, their applicability to SSL estimation in rivers has not yet been investigated. In this study, we evaluated use of a CART model to estimate SSL based on hydro-meteorological data. We also compared the accuracy of the CART model with that of the four most commonly used models for time series modelling of SSL, i.e. adaptive neuro-fuzzy inference system (ANFIS), multi-layer perceptron (MLP) neural network and two kernels of support vector machines (RBF-SVM and P-SVM). The models were calibrated using river discharge, stage, rainfall and monthly SSL data for the Kareh-Sang River gauging station in the Haraz watershed in northern Iran, where sediment transport is a considerable issue. In addition, different combinations of input data with various time lags were explored to estimate SSL. The best input combination was identified through trial and error, percent bias (PBIAS), Taylor diagrams and violin plots for each model. For evaluating the capability of the models, different statistics such as Nash-Sutcliffe efficiency (NSE), Kling-Gupta efficiency (KGE) and percent bias (PBIAS) were used. The results showed that the CART model performed best in predicting SSL (NSE=0.77, KGE=0.8, PBIAS<±15), followed by RBF-SVM (NSE=0.68, KGE=0.72, PBIAS<±15). Thus the CART model can be a helpful tool in basins where hydro-meteorological data are readily available.

A comparative study of three different learning algorithms applied to ANFIS for predicting daily suspended sediment concentration

The modeling and prediction of suspended sediment in a river are key elements in global water recourses and environment policy and management. In the present study, an Adaptive Neuro-Fuzzy Inference System model trained with the Levenberg-Marquardt learning algorithm is considered for time series modeling of suspended sediment concentration in a river. The model is trained and validated using daily river discharge and suspended sediment concentration data from the Schuylkill River in the United States. The results of the proposed method are evaluated and compared with similar networks trained with the common Hybrid and Back-Propagation algorithms, which are widely used in the literature for prediction of suspended sediment concentration. Obtained results demonstrate that models trained with the Hybrid and Levenberg-Marquardt algorithms are comparable in terms of prediction accuracy. However, the networks trained with the Levenberg-Marquardt algorithm perform better than those trained with the Hybrid approach.

Kármán vortex and turbulent wake generation by wind park piles

Observational evidence of turbulent wakes behind wind parks’ piles motivated a series of numerical experiments, aiming to identify the dynamic regimes associated with wakes’ generation in tidal basins. We demonstrate that the obstacles such as piles of wind parks give rise to vortices similar to the known Karman vortices which affect substantially the turbulent kinetic energy. The latter can be considered as the agent enhancing sediment remobilization from the ocean bottom, thus making wakes well visible in satellite data. The temporal and spatial variability of studied processes is analyzed under stationary and nonstationary conditions. The dependence of a vortex generation and evolution upon the environmental conditions is also studied, which demonstrates a large variety of appearances of turbulent wakes. The comparison between simulations using a suspended sediment model and satellite images demonstrated that the model is capable to realistically simulate sediment wakes observed in remote sensing data.

Modeling suspended sediment transport and assessing the impacts of climate change in a karstic Mediterranean watershed

Mediterranean semi-arid watersheds are characterized by a climate type with long periods of drought and infrequent but high-intensity rainfalls. These factors lead to the formation of temporary flow tributaries which present flashy hydrographs with response times ranging from minutes to hours and high erosion rates with significant sediment transport. Modeling of suspended sediment concentration in such watersheds is of utmost importance due to flash flood phenomena, during which, large quantities of sediments and pollutants are carried downstream. The aim of this study is to develop a modeling framework for suspended sediment transport in a karstic watershed and assess the impact of climate change on flow, soil erosion and sediment transport in a hydrologically complex and intensively managed Mediterranean watershed. The Soil and Water Assessment Tool (SWAT) model was coupled with a karstic flow and suspended sediment model in order to simulate the hydrology and sediment yield of the karstic springs and the whole watershed. Both daily flow data (2005–2014) and monthly sediment concentration data (2011–2014) were used for model calibration. The results showed good agreement between observed and modeled values for both flow and sediment concentration. Flash flood events account for 63–70% of the annual sediment export depending on a wet or dry year. Simulation results for a set of IPCC “A1B” climate change scenarios suggested that major decreases in surface flow (69.6%) and in the flow of the springs (76.5%) take place between the 2010–2049 and 2050–2090 time periods. An assessment of the future ecological flows revealed that the frequency of minimum flow events increases over the years. The trend of surface sediment export during these periods is also decreasing (54.5%) but the difference is not statistically significant due to the variability of the sediment. On the other hand, sediment originating from the springs is not affected significantly by climate change.

Lowland fluvial phosphorus altered by dams

AbstractDams affect ecosystems, but their physical link to the variations in fluvial fluxes and downstream ecological consequences are inadequately understood. After estimating the current effects of the Three Gorges project and other reservoirs upstream on the Yangtze River on the fluvial phosphorus (P) in the middle and lower Yangtze River, we further investigated the long‐term effects of dams on the fluvial regimes of P and P‐enriched sediment (PES). Simultaneously measured P distributions with sediment size (PDSS) from the Three Gorges Reservoir (TGR) proved that the areal density of particulate P (PP) bound on graded sediment can be measured using the surface area concentration of the total sediment. A PDSS relationship is obtained and the selective transport and long‐term sedimentation of P are simulated using a nonuniform suspended sediment model, which incorporates the PDSS formula. The computations revealed that a reservoir would significantly lower the downstream availability of P in the dry season and promote high pulses of P in summer when the reservoir is flushed as sedimentation accumulates. As a result, the P buffering and replenishing mechanism in the pristine ecosystem from upstream supplies and local re‐suspension are permanently eliminated when a regulating reservoir is built upstream. This change is irreversible if reservoir regulation continues. Changes could potentially aggravate the existing P‐limitation, decrease the water's ability to adjust nutrient/pollutant fluctuations, accumulate a greater surplus of carbon and nitrogen, and even exacerbate blooms in favorable conditions.

Simulation Method of Particle Size Scale for Fine Sand Model

In sediment movable bed model, the basic similar conditions include the flow movement similar and the sediment movement similar. In water flow movement similar conditions, the velocity scale of the Freund's similarity and resistance similarity is inconsistency, and the flow resistance is the function of bed material grain size and flow intensity. In sediment movement similar, the particle size scale forms are not consistent too, and they are also related to the flow conditions, so the sediment partial size scale is difficult to determine. According to the research, the similar conditions can be focused on primary and secondary one, and put the primary one as the design basis. In view of the waterway regulation, the regulation flow discharge should be the design basis, others allowed a certain deviation; In the straight reach, resistance similarity should be the design basis, Freund's similarity allowed a certain deviation; In the bend reach, the Freund's similarity and resistance similarity should be simultaneously satisfied; For the bed load model, the incipient motion should meet similarity condition; The suspended sediment model should meet the sediment suspension similarity; For the non-uniform sediment, median particle size should be the design basis. According to the above principles, the sediment particle size scale can be determined.

Numerical simulation of turbulence and sediment transport of medium sand

A model of sand transport in water is produced by combining a turbulence-resolving large eddy simulation (LES) with a discrete element model (DEM) prescribing the motion of individual grains of medium sand. The momentum effect of each particle on the fluid is calculated at the LES cell containing the particle, and the fluid velocity and pressure, interpolated to each particle center, is used to derive fluid force on each particle in the DEM. Eleven numerical experiments are conducted of an initially flat bed of particles. The experiments span a range of motion, from essentially no motion to vigorous suspension. Hydraulic roughness is found to increase abruptly at the transition from bed load to suspended load transport. Suspended sediment extracts momentum from the flow and decreases the rate of shear. Whereas, slightly higher in the flow, vertical drag by suspended grains damps turbulence and increases the rate of shear. Vertical sediment diffusivity and effective particle settling velocity are much smaller than is commonly assumed in suspended sediment models. The bed load experiments suggest that saltation by itself is a poor model of bed load sand transport. In contrast to expectations from saltation models, the peak bed load flux occurs at essentially the same level as the bed, and grains move slowly in frequent contact with other grains. Higher- and faster-moving bed load grains that can be considered to be in saltation represent a smaller portion of the total flux. Entrainment of bed load grains occurs in response to fluid penetration of the bed by high-vorticity turbulence structures embedded within broader high speed fluid regions referred to as a sweeps or high-speed wedges.

High-Density Mud Suspensions and Cross-Shelf Transport: On the Mechanism of Gelling Ignition

Abstract This study theoretically explores sediment fluxes of high-density mud suspensions across the seafloor under the assumption that the dispersions received their entire sediment load from local resuspension of surface mud. Flocculation is ignored, and a constant maximum floccule size is prescribed. The resultant sediment-flux equation, which constitutes a bottom-boundary condition for use in suspended-sediment models, has important physical implications. First, this study identifies a condition, referred to as gelling ignition, in which sediment concentrations will increase to extremely large values owing to a positive feedback between net erosion and hindered settling. Remarkably, this work reveals that, owing to boundary-layer dynamics, mud suspensions of both low and high concentrations are easier to keep in suspension than those of intermediate concentrations. Wave conditions in which high concentrations are produced in the model are within the realm of those typical of storms on shelves. On a sloping shelf, these highly concentrated suspended mud layers would be driven down slope by gravity, and thus represent a possible mechanism for cross-shelf transport.

Relevance Vector Machine Models of Suspended Fine Sediment Transport in a Shallow Lake—I: Data Collection

Mud Lake is part of a wildlife refuge located in southeastern Idaho and is operated by a power company to maximize power consumption, while providing for delivery of irrigation flows. Mud Lake is used as a sediment trap for the water flowing from the Bear River into the adjacent Bear Lake. This study explores the use of multivariable relevance vector machine (MVRVM) modeling to predict suspended fine sediment and other water quality constituent concentrations, and their spatial and temporal distribution. In this article, the first of two, we describe an experimental design and data collection program for the observations of water quality constituent data and hydraulic parameters to support creation of the MVRVM model. We briefly describe the MVRVM modeling approach, describe the development of the experimental program and the resulting observations, and finally discuss the suitability of the data to modeling with the MVRVM. Details of the MVRVM model and its application are provided in a second article. Success of the MVRVM will confirm the ability of statistical learning tools to predict sediment concentrations, and will lead the way for scientists to expand the use of the MVRVM for modeling of suspended fine sediment and water quality in other complex natural systems.

A weight-of-evidence approach to integrate suspended sediment source information

Sediment monitoring, tracing and modelling are widely used to identify suspended sediment sources. Although each method has inherent limitations and uncertainties, their integration provides opportunities to form collective knowledge and encourages robust management strategies. This paper presents a Weight-of-Evidence approach to integrate multiple Lines-of-Evidence for identifying suspended sediment sources. Three sources of evidence were used: i) stream flow and suspended sediment monitoring at river gauges; ii) geochemical sediment tracing at river junctions; and iii) catchment-scale suspended sediment modelling of hillslope, gully, streambank and unsealed road erosion. We applied this approach on two data-poor catchments in Australia. Some reaches were consistently identified as major sources of sediment from all Lines-of-Evidence. However, inconsistencies between the types of evidence in other areas highlighted the high uncertainty in identifying suspended sediment sources in these areas and the need for further investigation. The integration framework maximised the use of scarce information, enabled explicit consideration of uncertainties for catchment management and identified where future monitoring and research should be targeted.

A flux-limiter method for dam-break flows over erodible sediment beds

Finite volume methods for dam-break flows over erodible sediment beds require a monotone numerical flux. In the present study we present a new flux-limiter scheme based on the Lax–Wendroff method coupled with a non-homogeneous Riemann solver and a flux limiter function. The non-homogeneous Riemann solver consists of a predictor stage for the discretization of gradient terms and a corrector stage for the treatment of source terms. The proposed method satisfy the conservation property such that the discretization of the flux gradients and the source terms are well-balanced in the numerical solution of suspended sediment models. The flux-limiter method provides accurate results avoiding numerical oscillations and numerical dissipation in the approximated solutions. Several standard test examples are considered to verify the performance and the accuracy of the proposed method.