Physical explanations of variations in river meander migration rates from model comparison

Crosato, Alessandra

doi:10.1002/esp.1898

Cited by 50 publications

(55 citation statements)

References 20 publications

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“…Previous research has indicated that complex flow patterns around meander bends drastically modify the expected shear stress distribution from the assumption of steady, uniform flow (Papanicolaou et al, 2007;Pizzuto, 2008). Using Crosato's (2007) "no-lag kinematic model" predicted an increased boundary shear stress (up to 2.5 times at peak flow) but resulted in no additional bank retreat than the same simulation with the excess shear stress equation. More sophisticated formulations can be used to increase the boundary shear stress, as it was hypothesized that applied shear stresses are still under predicted, but this is again dependent on data to represent this process.…”

Section: Modeling Bank Retreatmentioning

confidence: 89%

“…Papanicolaou et al (2007) suggested that due to secondary currents the bottom half of the streambank may experience stress distributions two to three times higher than the shear stress calculated by first order approximations. In BSTEM, the boundary shear stress is corrected for the effects of curvature using the "no-lag kinematic model" (Crosato, 2007):…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of the bank stability and toe erosion model (BSTEM) for predicting lateral retreat on composite streambanks

2012

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Section: Modeling Bank Retreatmentioning

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Evaluation of the bank stability and toe erosion model (BSTEM) for predicting lateral retreat on composite streambanks

2012

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“…Shear stress is typically greater in the outside of meander bends due to higher maximum velocities near the bank, super-elevation of the water surface, and secondary currents directed towards the bank (Knighton, 1998). BSTEM accounts for these effects by adjusting the average boundary shear stress (Crosato, 2009(Crosato, , 2007:…”

Section: A1 Bstem Summarymentioning

confidence: 99%

Uncertainty and sensitivity in a bank stability model: implications for estimating phosphorus loading

Lammers

Bledsoe

Langendoen

2016

Earth Surf Processes Landf

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UNCERTAINTY AND SENSITIVITY IN A BANK STABILITY MODEL: IMPLICATIONS FOR ESTIMATING PHOSPHORUS LOADINGEutrophication of aquatic ecosystems is one of the most pressing water quality concerns in the U.S. and around the world. Bank erosion has been largely overlooked as a source of nutrient loading, despite field studies demonstrating that this source can account for the majority of the total phosphorus budget of a watershed. Substantial effort has been made to develop mechanistic models to predict bank erosion and instability in stream systems; however, these models do not account for inherent natural variability in input values. Providing only single output values with no quantification of associated uncertainty can complicate management decisions focused on reducing bank erosion and nutrient loading to streams. To address this issue, uncertainty and sensitivity analyses were performed on the Bank Stability and Toe Erosion Model (BSTEM), a mechanistic model developed by the USDA-ARS that simulates both mass wasting (stability) and fluvial erosion of streambanks. Sensitivity analysis results indicate that variable influence on model output can vary depending on assumed input distributions.Generally, bank height, soil cohesion, and plant species were found to be most influential in determining stability of clay (cohesive) banks. In addition to these three inputs, groundwater elevation, stream stage, and bank angle were also identified as important in sand (non-cohesive) banks. Slope and bank height are the dominant variables in fluvial erosion modeling, while erodibility and critical shear stress are relatively unimportant. However, the threshold effect of critical shear stress (determining whether erosion occurs) was not explicitly accounted for, ii possibly explaining the relatively low sensitivity indices for this variable. Model output distributions of sediment and phosphorus loading rates corresponded well to ranges published in the literature, helping validate both model performance and selected ranges of input values. In addition, a probabilistic modeling approach was applied to data from a watershed-scale sediment and phosphorus loading study on the Missisquoi River, Vermont to quantify uncertainty associated with these published results. While our estimates indicated that bank erosion was likely a significant source of sediment and phosphorus to the watershed in question, the uncertainty associated with these predictions indicates that they should probably be considered order of magnitude estimates only.iii ACKNOWLEDGEMENTS

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“…The mathematical model adopted in this study, Miandras (Crosato, 1987(Crosato, , 2008(Crosato, , 2009, computes the longitudinal profiles of the nearbank excesses of flow velocity and water depth, U and H, respectively, with respect to the reach-averaged values, u 0 and h 0 ( Figure 3). These excesses are caused by the local channel curvature and by upstream geometrical discontinuities such as a change of channel curvature (bend entrance and exit), which, under certain conditions lead to the formation of steady alternate bars in the river channel (Struiksma et al, 1985).…”

Section: Channel Migration Modelmentioning

confidence: 99%

“…A full model description is given by Crosato (1987Crosato ( , 2007Crosato ( , 2008Crosato ( , 2009). …”

Section: Water Managementmentioning

confidence: 99%

Variable input parameter influence on river corridor prediction

Zerfu¹,

Beevers²,

Crosato³

et al. 2015

Proceedings of the Institution of Civil Engineers - Water Manag

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This paper considers the erodible river corridor, which is the area in which the main river channel is free to migrate over a period of time. Due to growing anthropogenic pressure, predicting the corridor width has become increasingly important for the planning of development along rivers. Several approaches can be used to predict the future erodible corridor width but the results possess a large degree of uncertainty in all cases. The work presented here addresses prediction of the erodible corridor width of a reach of the River Irwell, UK, taking into account the uncertainty that arises from input parameters such as representative discharge, channel width, sediment and so on.The work adopts a probabilistic framework for assessment using Monte Carlo type simulations. Future river corridor width predictions, based on a model calibrated on past observations, are presented in a probabilistic manner using confidence levels. The results indicate the necessity of capturing input variability in the modelling process.Furthermore, the understanding gained from a relatively simple model used in a probabilistic framework is greater than a more complex one where only a few runs are feasible.

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Physical explanations of variations in river meander migration rates from model comparison

Cited by 50 publications

References 20 publications

Evaluation of the bank stability and toe erosion model (BSTEM) for predicting lateral retreat on composite streambanks

Evaluation of the bank stability and toe erosion model (BSTEM) for predicting lateral retreat on composite streambanks

Uncertainty and sensitivity in a bank stability model: implications for estimating phosphorus loading

Variable input parameter influence on river corridor prediction

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