A new formula for predicting movable bed roughness coefficient in the Middle Yangtze River

Computing movable bed roughness plays an important role in the modeling of flood routing and bed deformation, and the magnitude of movable bed roughness is closely associated with complex bedform configurations that change with the sand wave motion. The motion of sand wave is dependent on the incoming flow and sediment conditions and channel boundary. After the operation of the Three Gorges Project, the flow and sediment regime changed remarkably in the Middle Yangtze River (MYR), followed by significant channel adjustments. A dramatic decrease in sediment concentration caused continuous channel degradation and significant variations in cross-sectional profiles of the MYR. These adjustments in the channel boundary influence the motion of sand wave, which can further affect the magnitude of movable bed roughness. A new formula for predicting the movable bed roughness coefficient is developed, which can be expressed by a power function of both Froude number and relative water depth. The proposed formula was first calibrated using 1266 datasets of measurements at five hydrometric stations in the MYR during 2001–2012. A back-calculation process shows that the roughness coefficients calculated by the proposed formula agree well with the observations, with the determination coefficient being equal to 0.88. The proposed formula was further verified using 651 datasets of measurements at these hydrometric stations during 2013–2017. Furthermore, four common roughness formulas selected from the literature were tested for comparison. The results indicate that the calculation accuracy of the proposed formula is significantly higher than that of the previous formulas, and the Manning roughness coefficients predicted by the proposed formula have the errors less than ±30% for 96% of the datasets. Therefore, the new bed roughness predictor proposed in this study can accurately calculate the roughness coefficients straightforwardly without iterative solution and graphical interpolation, and the parameters required in the roughness predictor are easily obtained from the hydrometric observations.

Flow Resistance in Lowland Rivers Impacted with Distributed Aquatic Vegetation

The study addresses the research concern that the employment of fixed value for bed roughness coefficient in lowland rivers (mostly ‌sand-bed rivers) is deemed practically questionable in the presence of a mobile bed and time-dependent changes in vegetation patches. To address this issue, we set up 45 cross-sections in four lowland streams to investigate seasonal flow resistance values within a year. The results first revealed that the significant sources of boundary resistance in lowland rivers with lower regime flow are bed forms and aquatic vegetation. Then, the study uses flow discharge as an influential variable reflecting the impacts of the above-mentioned sources of resistance to flow. The studied approach ended up with two new flow resistance predictors which simply connect dimensionless unit discharge with flow resistance factors, Darcy-Weisbach (f) and Manning (n) coefficients. A comparison between the computed and measured flow resistance values indicates that 87-89% of data sets were within the ±20% error bands. The flow resistance predictors are also verified against large independent sets of field and flume data. The obtained predictions using the developed predictors may overestimate flow resistance factors to about 40% for other lowland rivers. From a different view of this research, the findings on seasonal variation of vegetation abundance hint at the augmentation in flow resistance values, both f, and n, in low summer flows when the vegetation covers river bed and side banks. The highest amount of flow resistance was observed during the summer period, July-August.

Using bed-roughness signatures to characterise glacial landform assemblages beneath palaeo-ice sheets

Palaeo-glacial landforms can give insights into bed roughness that currently cannot be captured underneath contemporary-ice streams. A few studies have measured bed roughness of palaeo-ice streams but the bed roughness of specific landform assemblages has not been assessed. If glacial landform assemblages have a characteristic bed-roughness signature, this could potentially be used to constrain where certain landform assemblages exist underneath contemporary-ice sheets. To test this, bed roughness was calculated along 5 m × 5 m resolution transects (NEXTMap DTM, 5 m resolution), which were placed over glacial landform assemblages (e.g. drumlins) in the UK. We find that a combination of total roughness and anisotropy of roughness can be used to define characteristic roughness signatures of glacial landform assemblages. The results show that different window sizes are required to determine the characteristic roughness for a wide range of landform types and to produce bed-roughness signatures of these. Mega scale glacial lineations on average have the lowest bed-roughness values and are the most anisotropic landform assemblage.

Prediction of Hydraulic Jumps on a Triangular Bed Roughness Using Numerical Modeling and Soft Computing Methods

This study investigates the characteristics of free and submerged hydraulic jumps on the triangular bed roughness in various T/I ratios (i.e., height and distance of roughness) using CFD modeling techniques. The accuracy of numerical modeling outcomes was checked and compared using artificial intelligence methods, namely Support Vector Machines (SVM), Gene Expression Programming (GEP), and Random Forest (RF). The results of the FLOW-3D® model and experimental data showed that the overall mean value of relative error is 4.1%, which confirms the numerical model’s ability to predict the characteristics of the free and submerged jumps. The SVM model with a minimum of Root Mean Square Error (RMSE) and a maximum of correlation coefficient (R2), compared with GEP and RF models in the training and testing phases for predicting the sequent depth ratio (y2/y1), submerged depth ratio (y3/y1), tailwater depth ratio (y4/y1), length ratio of jumps (Lj/y2*) and energy dissipation (ΔE/E1), was recognized as the best model. Moreover, the best result for predicting the length ratio of free jumps (Ljf/y2*) in the optimal gamma is γ = 10 and the length ratio of submerged jumps (Ljs/y2*) is γ = 0.60. Based on sensitivity analysis, the Froude number has the greatest effect on predicting the (y3/y1) compared with submergence factors (SF) and T/I. By omitting this parameter, the prediction accuracy is significantly reduced. Finally, the relationships with good correlation coefficients for the mentioned parameters in free and submerged jumps were presented based on numerical results.

A Bidimensional Model of the Tagliamento River

The propagation of a flood wave is a very challenging topic, crucial in managing the flood risk. In the literature, several numerical models have been proposed to deal with this issue; most of them need the roughness coefficients to be assigned by the operator. The bottom roughness calibration of floodplains and channels represents a key point for flood studies, because it can heavily influence the results of any kind of numerical simulation. In this study, a numerical model is applied to the Tagliamento River, in North-East Italy. One of the main characteristics of this river is its natural environment, which changes from a very wide braided channel in the middle course to a narrow meandering river moving towards the sea. This makes the bed roughness extremely variable along the river, with different kind of vegetation, braiding, different grain size, meandering, etc. In this regard, particular care should be devoted to the roughness coefficient attribution and calibration. In the present paper, we present the detailed step of calibration and validation of a bidimensional numerical model on the Tagliamento River. A novel method to assign and calibrate roughness coefficient is introduced. Finally, the model is validated against two main flood events occurred in 1966 and 1996.

Sediment shell-content diminishes current-driven sand ripple development and migration

Shells and shell fragments are biogenic structures that are widespread throughout natural sandy shelf seas and whose presence can affect the bed roughness and erodibility of the seabed. An important and direct consequence is the effect on the formation and movement of small bedforms such as sand ripples. We experimentally measured ripple formation and the migration of a mixture of natural sand with increasing volumes of shell material in a racetrack flume. Our experiments reveal the impacts of shells on ripple development in sandy sediment, providing information that was previously lacking. Shells expedite the onset of sediment transport while simultaneously reducing ripple dimensions and slowing down their migration rates. Moreover, increasing shell content enhances near-bed flow velocity due to the reduction of bed friction that is partly caused by a decrease in average ripple size and occurrence. This, in essence, limits the rate and magnitude of bed load transport. Given the large influence of shell content on sediment dynamics as well as the high shell concentrations found naturally in the sediments of shallow seas, a significant control from shells on the morphodynamics of sandy marine habitats is expected.