Quantifying the effect of riparian forest versus agricultural vegetation on river meander migration rates, central Sacramento River, California, USA

2004 ◽  
Vol 20 (5) ◽  
pp. 537-548 ◽  
Author(s):  
E. R. Micheli ◽  
J. W. Kirchner ◽  
E. W. Larsen
2021 ◽  
Author(s):  
Hossein amini ◽  
Guido Zolezzi ◽  
Federico Monegaglia ◽  
Emanuele Olivetti ◽  
Marco Tubino

<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>


2007 ◽  
Vol 86 (3) ◽  
pp. 257-271 ◽  
Author(s):  
H.P. Wolfert ◽  
G.J. Maas

AbstractThe morphodynamics of the lower River Vecht, the Netherlands, and the influence of geomorphological setting and bank composition on meander migration were studied by means of reconstructing the pre-channelization landform configuration on a scale of 1 : 25,000, using historical maps from 1720, 1850 and 1890 A.D. and other data.A downstream sequence of reaches was observed, each with a typical fluvial style and channel migration rate: (a) a narrow meander belt and a highly sinuous channel with intermediate migration rate, in the middle of an extensive floodbasin; (b) a wide meander belt and high rates of lateral channel migration, especially where large meanders impinged upon valley bluffs, as part of an incised setting; (c) a low sinuosity, embanked channel with low rates of downstream migration because of confinement by dikes, occurring in an inland delta with sandy sediments.Local variation in meander migration rates was observed within reach B. This was caused by the spatial variability of bank resistance as reflected by the width-depth ratio of the channel and the silt-clay ratios of deposits. River banks are: 1) very erodible when consisting of channel deposits, aeolian dune deposits or when coarse fluvio-periglacial deposits occur at their base; 2) erodible when dominated by overbank deposits or aeolian sand sheet deposits; 3) resistant when a plaggen-layer is exposed; and 4) very resistant when dominated by floodbasin deposits.These implications of meander variability enable to assess the effects of the rehabilitation of the meandering process.


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