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

Annual sediment flux estimates in a tidal strait using surrogate measurements

Tidal fluxes of nutrients and suspended sediments at the North Inlet–Winyah Bay National Estuarine Research Reserve

Large-eddy simulations (LES) are an important tool for investigating the longstanding energy-balance-closure problem, as they provide continuous, spatially-distributed information about turbulent flow at a high temporal resolution. Former LES studies reproduced an energy-balance gap similar to the observations in the field typically amounting to 10–30% for heights on the order of 100 m in convective boundary layers even above homogeneous surfaces. The underestimation is caused by dispersive fluxes associated with large-scale turbulent organized structures that are not captured by single-tower measurements. However, the gap typically vanishes near the surface, i.e. at typical eddy-covariance measurement heights below 20 m, contrary to the findings from field measurements. In this study, we aim to find a LES set-up that can represent the correct magnitude of the energy-balance gap close to the surface. Therefore, we use a nested two-way coupled LES, with a fine grid that allows us to resolve fluxes and atmospheric structures at typical eddy-covariance measurement heights of 20 m. Under different stability regimes we compare three different options for lower boundary conditions featuring grassland and forest surfaces, i.e. (1) prescribed surface fluxes, (2) a land-surface model, and (3) a land-surface model in combination with a resolved canopy. We show that the use of prescribed surface fluxes and a land-surface model yields similar dispersive heat fluxes that are very small near the vegetation top for both grassland and forest surfaces. However, with the resolved forest canopy, dispersive heat fluxes are clearly larger, which we explain by a clear impact of the resolved canopy on the relationship between variance and flux–variance similarity functions.

<p>Quantitative knowledge of the surface energy balance is essential for the prediction of weather and climate. However, a multitude of studies from around the world indicates that the turbulent heat fluxes are generally underestimated using eddy-covariance measurements, and hence, the surface energy balance is not closed. This energy balance closure problem has been heavily covered in the literature for more than 25 years, and as a result, several instrumental and methodological aspects have been reconsidered and partially revised. Nevertheless, a non-negligible energy imbalance remains, and we demonstrate that a major portion of this imbalance can be explained by dispersive fluxes in the surface layer, which are associated with submesoscale secondary circulations. Such large-scale organized structures are a very common phenomenon in the convective boundary layer, and depending on static stability, they can either be roll-like or cell-like and occur even over homogeneous surfaces. Over heterogeneous surfaces, thermally-induced mesoscale circulations can occur in addition to those. Either way, the associated dispersive heat fluxes can inherently not be captured by single-tower measurements, since the ergodicity assumption is violated. As a consequence, energy transported non-turbulently will not be sensed by eddy-covariance systems and a bias towards lower energy fluxes will result. The objective of this research is to develop a model that can be used to correct single-tower eddy-covariance data. As a first step towards this goal, we will present a parametrisation for dispersive fluxes, which was developed based on an idealized high-resolution LES study for homogeneous surfaces, as a function of non-local scaling variables. Secondly, we explore how well this parametrisation works for a number of real-world eddy-covariance sites.</p>

High suspended sediment (SPS) concentration exists in many rivers of the world. In the present study, the effects of SPS concentration on denitrification were investigated in airtight chambers with sediment samples collected from the Yellow River which is the largest turbid river in the world. Results from the nitrogen stable ((15)N) isotopic tracer experiments showed that denitrification could occur on SPS in oxic waters and the denitrification rate increased with SPS concentration; this was probably caused by the presence of low-oxygen microsites in SPS. For the water systems with both bed-sediment and SPS, the denitrification kinetics fit well to Logistic model, and the denitrification rate constant increased linearly with SPS concentration (p < 0.01). The denitrification caused by the presence of SPS accounted for 22%, 38%, 53%, and 67% of the total denitrification in systems with 2.5, 8, 15, and 20 g L(-1) SPS, respectively. The activity of denitrifying bacteria in SPS was approximately twice that in bed-sediment, and the denitrifying bacteria population showed an increasing trend with SPS concentration in both SPS and bed-sediment, leading to the increase of denitrification rate with SPS concentration. Furthermore, the denitrification in bed-sediment was accelerated by increased diffusion of nitrate from overlying water to bed-sediment under agitation conditions, which accompanied with the presence of SPS. When with 8 g L(-1) SPS, approximately 66% of the increased denitrification compared to that without SPS was attributed to denitrification on SPS and 34% to agitation conditions. This is the first report of the occurrence of denitrification on SPS in oxic waters. The results suggest that SPS plays an important role in denitrification in turbid rivers; its effect on nitrogen cycle should be considered in future study.

Large-eddy simulations are conducted to contrast momentum and passive scalar transport over large, three-dimensional roughness elements in a turbulent channel flow. Special attention is given to the dispersive fluxes, which are shown to be a significant fraction of the total flux within the roughness sublayer. Based on pointwise quadrant analysis, the turbulent components of the transport of momentum and scalars are found to be similar in general, albeit with increasing dissimilarity for roughnesses with low frontal blockage. However, strong dissimilarity is noted between the dispersive momentum and scalar fluxes, especially below the top of the roughness elements. In general, turbulence is found to transport momentum more efficiently than scalars, while the reverse applies to the dispersive contributions. The effects of varying surface geometries, measured by the frontal density, are pronounced on turbulent fluxes and even more so on dispersive fluxes. Increasing frontal density induces a general transition in the flow from a wall bounded type to a mixing layer type. This transition results in an increase in the efficiency of turbulent momentum transport, but the reverse occurs for scalars due to reduced contributions from large-scale motions in the roughness sublayer. This study highlights the need for distinct parameterizations of the turbulent and dispersive fluxes, as well as the importance of considering the contrasts between momentum and scalar transport for flows over very rough surfaces.

The U.S. Geological Survey, in cooperation with the Vermont Department of Environmental Conservation, investigated the use of acoustic backscatter to estimate concentrations of suspended sediment and total phosphorus at the Barton River near Coventry, Vermont. The hypothesis was that acoustic backscatter—the reflection of sound waves off objects back to the source from which they came—measured by an acoustic Doppler profiler (ADP) and recorded as ancillary data for the calculation of discharge, also could be used to generate a continuous concentration record of suspended sediment and phosphorus at the streamgage, thereby deriving added value from the instrument. Suspended-sediment and phosphorus concentrations are of particular interest in Vermont, where impairment of surface waters by suspended sediments and phosphorus is a major concern. Regression models for estimating suspended-sediment concentrations (SSCs) and total phosphorus concentrations evaluated several independent variables: measured backscatter (MB), water-corrected backscatter (WCB), sediment-corrected backscatter (SCB), discharge, fluid-absorption coefficient, sediment-driven acoustic attenuation coefficient, and discharge hysteresis. The best regression equations for estimating SSC used backscatter as the predictor, reflecting the direct relation between acoustic backscatter and SSC. Backscatter was a better predictor of SSC than discharge in part because hysteresis between SSC and backscatter was less than for SSC and discharge. All three backscatter variables—MB, WCB, and SCB— performed equally as predictors of SSC and phosphorus concentrations at the Barton River site. The similar abilities to predict SSC among backscatter terms may partially be attributed to the low values and narrow range of the sediment-driven acoustic attenuation in the Barton River. The regression based on SCB was selected for estimating SSC because it removes potential bias caused by attenuation and temperature fluctuations. The best regression model for estimating phosphorus concentrations included terms for discharge and discharge hysteresis. The finding that discharge hysteresis was a significant predictor of phosphorus concentrations might be related to preferential sorption of phosphorus to fine-grained sediments, which have been found to be particularly sensitive to hysteresis. Regression models designed to estimate phosphorus concentrations had less predictive power than the models for SSCs. Data from the Barton River did not fully support one of the study’s hypotheses—that backscatter is mostly caused by sands, and attenuation is mostly caused by fines. Sands, fines, and total SSCs in the Barton River all related better to backscatter than to sediment-driven acoustic attenuation. The weak relation between SSC and sediment-driven acoustic attenuation may be related to the low values and narrow range of SSCs and sediment attenuations observed at Barton River. A weak relation between SSC and sediment-driven acoustic attenuation also suggests that the diameters of the fine-sized suspended sediments in the Barton River may be predominantly greater than 20 micrometers (μm). Long-term changes in the particle-size distribution (PSD) were not observed in Barton River; however, some degree of within-storm changes in sediment source and possibly PSD were inferred from the hysteresis between SSC and SCB.

Dissolved organic nitrogen transformation in river water: Effects of suspended sediment and organic nitrogen concentration

Acoustic turbulence measurements of near-bed suspended sediment dynamics in highly turbid waters of a macrotidal estuary

Most mesoscale models are developed with grid resolution in the range of kilometers. Therefore, they may require spatial averaging to analyze flow behavior over the domain of interest. In doing so, certain important features of sub-grid scales are lost. Moreover, spatial averaging on the governing equations results in additional terms known as dispersive fluxes. These fluxes are ignored in the analysis. The aim of this paper is to identify the significance of these fluxes for accurate assessment of flow fields related to wind farm applications. The research objectives are hence twofold: 1) to quantify the impact of wind turbines on MBL characteristics. 2) to account for the magnitude of dispersive fluxes arising from spatial averaging and make a comparison against the turbulent flux values. To conduct the numerical study the NREL 5MW reference wind turbine model is employed with a RANS approach using k-ε turbulence model. The results are presented concerning spatially averaged velocity, wake deficit behind the turbine, dispersive and turbulent fluxes.

Effect of policy-induced measures on suspended sediments and total phosphorus concentrations from three Norwegian agricultural catchments

&amp;lt;p&amp;gt;More than half of the world population lives in cities. It is imperative to improve our predictive understanding of the urban boundary layer. In particular, considerable knowledge gaps still exist in turbulent transport of scalars (temperature, moisture and air pollutants) over urban rough surfaces, especially in the urban roughness sublayers. Using obstacle-resolving large eddy simulations, we first compare and contrast momentum and passive scalar transport over large, three-dimensional roughness elements. Dispersive scalar fluxes are shown to be a significant fraction of the total fluxes within the roughness sublayers. Strong dissimilarity is also noted between the dispersive momentum and scalar fluxes. The results highlight the need for distinct parameterizations of the turbulent and dispersive fluxes, as well as the importance of considering the contrasts between momentum and scalar transport for flows over very rough surfaces. In addition, the links between momentum and scalar roughness lengths (z&amp;lt;sub&amp;gt;0m&amp;lt;/sub&amp;gt; and z&amp;lt;sub&amp;gt;0s&amp;lt;/sub&amp;gt;) are explored by developing a conceptual framework that considers z&amp;lt;sub&amp;gt;0m&amp;lt;/sub&amp;gt; and z&amp;lt;sub&amp;gt;0s &amp;lt;/sub&amp;gt;at two distinct scales, namely micro and macro scales. Using a surface renewal theory for macro-scale roughness lengths, a log(z&amp;lt;sub&amp;gt;0m&amp;lt;/sub&amp;gt;/z&amp;lt;sub&amp;gt;os&amp;lt;/sub&amp;gt;) scaling with Re&amp;lt;sub&amp;gt;*&amp;lt;/sub&amp;gt;&amp;lt;sup&amp;gt;1/2&amp;lt;/sup&amp;gt; is predicted and is supported by LES results. Overall, these results underline the potential of using wall-modeled, large-obstacle resolving LES to improve our process-based understanding, as well as to identify and represent the missing first-order physical processes in the ABL. &amp;amp;#160;&amp;amp;#160;&amp;lt;/p&amp;gt;

Using ADV backscatter strength for measuring suspended cohesive sediment concentration

High suspended sediment (SPS) concentrations exist in many Asian river systems. In this research, the effects of SPS concentration on nitrification in river water systems were studied. With orwithout introducing ammonium-oxidizing bacteria isolated from the water and sediment samples of the Yellow River, the microbially mediated nitrification rate increased with SPS concentration as described by the power function y = a x x(b), where y is the nitrification rate, x is the SPS concentration, and a and b are constants. With an indigenous ammonium-oxidizing bacteria, nitrification rate constants, i.e., K4 (micromax/Ks) values obtained from the Monod model, were 0.0016, 0.0036, 0.0040, 0.0063, 0.0066, 0.0071, and 0.0077 day(-1) microM(-1) for the systems with SPS concentrations of 0, 0.2 1.0, 5.0, 10, 20, and 40 g/L, respectively. The sorption percentage of NH4+-N increased with SPS concentration as a power function. Bacteria tend to attach onto SPS, and the maximum specific growth rate at the SPS-water interface was about twice that in the water phase. An increase of bacterial population and nitrification rate constant with SPS as a power function resulted in an increase of nitrification rate with SPS as a power function. Therefore, the high SPS concentration caused by erosion and bottom sediment resuspension and other factors will accelerate ammonium oxidation in many turbid river systems. This has useful implications for nitrogen removal from river systems.

Suspended sediment dynamics play an important role in controlling nearshore and estuarine geomorphology and the associated ecological environments. Modeling the transport of suspended sediment is a complicated and challenging research topic. The goal of this study is to improve the accuracy of modeling the suspended sediment concentrations (SSCs) with newly developed techniques. Based on a three-dimensional suspended cohesive sediment transport model, the transport of suspended sediment and SSCs are simulated by assimilating SSCs retrieved from the Geostationary Ocean Color Imager (GOCI) with the adjoint data assimilation in the Hangzhou Bay, a typical strong tidal estuary along the coast of the East China Sea. To improve the effect of the data assimilation, the penalty function method, in which the reasonable constraints of the estimated model parameters are added to the cost function as penalty terms, will be introduced for the first time into the adjoint data assimilation in the SSCs modeling. In twin experiments, the prescribed spatially varying settling velocity is estimated by assimilating the synthetic SSC observations, and the results show that the penalty function method can further improve the effect of data assimilation and parameter estimation, regardless of synthetic SSC observations being contaminated by random artificial errors. In practical experiments, the spatially varying settling velocity is firstly estimated by assimilating the actual GOCI-retrieved SSCs. The results demonstrate that the simulated results can be improved by the adjoint data assimilation, and the penalty function method can additionally reduce the mean absolute error (MAE) between the independent check observations and the corresponding simulated SSCs from 1.44 × 10−1 kg/m3 to 1.30 × 10−1 kg/m3. To pursue greater simulation accuracy, the spatially varying settling velocity, resuspension rate, critical shear stress and initial conditions are simultaneously estimated by assimilating the actual GOCI-retrieved SSCs to simulate the SSCs in the Hangzhou Bay. When the adjoint data assimilation and the penalty function method are simultaneously used, the MAE between the independent check observations and the corresponding simulated SSCs is just 9.90 × 10−2 kg/m3, which is substantially less than that when only the settling velocity is estimated. The MAE is also considerably less than that when the four model parameters are estimated to be without using the penalty function method. This study indicates that the adjoint data assimilation can effectively improve the SSC simulation accuracy, and the penalty function method can limit the variation range of the estimated model parameters to further improve the effect of data assimilation and parameter estimation.