Upstream and downstream morphodynamic influence in simulated and real meandering rivers

<p>This study investigates the dependency of meander lateral migration rates on the spatial distribution of channel centerline curvature in both synthetic and real meandering rivers. It employs Machine Learning techniques (hereafter ML) to relate observed local lateral meander migration rates with the local and the upstream/downstream values of the centerline curvature. To achieve this goal, it was primarily essential to identify the feasibility of using ML in the meandering river's morphodynamics. We then determined the ability of ML to predict the excess near bank velocity based a set of input data using different regression techniques (linear and polynomial, Stochastic Gradient Descent, Multi-Layer Perceptron, and Support Vector Machine). We then moved forward to study the upstream-downstream influence on local migration rate. Synthetic meandering river planforms, as obtained through the planform evolution model of Bogoni et al. (2017), which is based on Zolezzi and Seminara (2001) meander flow model, were used as test cases for the calibration and check of the different adopted ML algorithms. The calibrated algorithms were then applied to multi-temporal information on meander planform dynamics obtained through the PyRiS software (Monegaglia et al., 2018), to quantify to which extent the upstream and downstream distribution of meander centerline curvature affects the local meander migration rate in real rivers.</p><p>References </p><p>1- Zolezzi, G., & Seminara, G. (2001b). Downstream and upstream influence in river meandering. Part 1. General theory and application overdeepening. Journal of Fluid Mechanics, 438(September 2015), 183–211. https://doi.org/10.1017/S002211200100427X</p><p>2- Monegaglia, F., Zolezzi, G., Güneralp, I., Henshaw, A. J., & Tubino, M. (2018). Automated extraction of meandering river morphodynamics from multitemporal remotely sensed data. In Environmental Modelling & Software (Vol. 105, pp. 171–186). https://doi.org/10.1016/j.envsoft.2018.03.028</p><p>3- Bogoni, M., Putti, M., & Lanzoni, S. (2017). Modeling meander morphodynamics over self-formed heterogeneous floodplains. In Water Resources Research (Vol. 53, Issue 6, pp. 5137–5157). https://doi.org/10.1002/2017wr020726</p><p>4- Benozzo, D.,  Olivetti, E., Avesani, P. (2017). Supervised Estimation of Granger-Based Causality between Time series. In Frontiers in Neuroinformatics. </p><p>https://doi.org/10.3389/fninf.2017.00068 </p><p>5- Sharma A., Kiciman, E. (2020). DoWhy: An End-to-End library for Causal Inference. arXiv preprint arXiv:2011.04216. </p><p>https://arxiv.org/abs/2011.04216</p>

Coupled Model of Bank Erosion and Meander Evolution for Cohesive Riverbanks

In this paper, a physics-based model that couples a bank erosion model with a meander evolution model is developed and evaluated. The physics-based bank erosion model considers the cantilever failure mechanism with slump blocks and decomposition effects. Moreover, bank accretion was considered using critical values of time required for landing, shear stresses and water depths. Two cases were tested. The first case consists of a hypothetical small-scale channel with cohesive riverbanks. Cross sections in the straight and curved part of the channel were compared to evaluate the curvature effect. Furthermore, the effect of the bank strength in the plan shape of the channel was tested in this case. The results show that the curvature increases the erosion rate in the outer bank and changes the cross-sectional profile by narrowing and widening the channel width. The plan shape of the channel changed as the bank strength was increased. In the second case, the model is compared with the River meander migration software (RVR meander) and the advantages and limitations of the model are discussed in terms of meander migration plan form and bank erosion processes. The results showed that the presented model is capable of simulating asymmetric bends.

Numerical modelling of cantilever failure and effect of slump blocks on meander migration

This study proposes a new numerical model to study cantilever failures and the effect of slump blocks on meander migration in cohesive river banks. Previous models have incorporated the effect of slump blocks using different methodologies but most of them used an “indirect approach” (such as increasing the critical shear stresses or introducing armouring factors) which does not allow to evaluate the effect of slump blocks directly. The new numerical model introduces an explicit representation of slump blocks and it was obtained by coupling two models available on the literature. The model was able to represent the mechanisms of cantilever failure with slump blocks and their effect in meander migration in a hypothetical small scale channel.

Meander migration: the observation method

River meanders migrate over time and the consequences of this migration can create a problem for bridges and embankments near the river. This is why it is important to predict the lateral extent of future migration over the life of neighboring infrastructure. In the observation method for meander migration (OMM), the past movement and velocity history of the meander are used to back-calculate site specific erosion parameters. Those parameters serve as input to predict the meander migration for a chosen future velocity hydrograph. In this article and after a review of existing knowledge, the analytical steps leading to the development of the OMM are described, then the field and laboratory work at four full-scale meander migration case histories are presented, and then the four full-scale meander migration case histories are used to evaluate the OMM. The OMM has been automated in an Excel spreadsheet.