2021
DOI: 10.1016/j.catena.2020.104917
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Predictive models for the estimation of riverbank erosion rates

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Cited by 21 publications
(9 citation statements)
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“…The five sub‐reaches where woody riparian and floodplain vegetation is sparse show significant differences in their response to the 2019–2020 events (Table 3) with reach‐scale detrimental changes, such as the reworking, remobilisation and redeposition of exposed and partially vegetated sediments, becoming superimposed on more expectable year‐on‐year incremental meandering activity through lateral bank erosion. All the sub‐reaches showed enhanced rates of bank erosion during the period when the events occurred with an expected variation in the data related to such factors as bend curvature, bank geometry bank strength and resistance (Arnez Ferrel et al, 2018; Saadon et al, 2021).…”
Section: Discussionmentioning
confidence: 96%
“…The five sub‐reaches where woody riparian and floodplain vegetation is sparse show significant differences in their response to the 2019–2020 events (Table 3) with reach‐scale detrimental changes, such as the reworking, remobilisation and redeposition of exposed and partially vegetated sediments, becoming superimposed on more expectable year‐on‐year incremental meandering activity through lateral bank erosion. All the sub‐reaches showed enhanced rates of bank erosion during the period when the events occurred with an expected variation in the data related to such factors as bend curvature, bank geometry bank strength and resistance (Arnez Ferrel et al, 2018; Saadon et al, 2021).…”
Section: Discussionmentioning
confidence: 96%
“…This study emphasizes the significance of the data population in developing prediction models employing mathematical, statistical, and artificial intelligence systems (Saadon et al, 2021;Saadon et al, 2020;Dobbin and Simon, 2011). The data splitting approach used in this research involved optimal split proportions, where 60% of the data was allocated for constructing the discharge rating curve, and the remaining 40% was dedicated to model validation.…”
Section: Methodsmentioning
confidence: 99%
“…Values within the range of 0.5 to 2.0 are considered accurate. This evaluation method has been widely employed in previous studies, including those by Ibrahim et al (2017), Sinnakaudan et al (2010), Saadon et al (2021Saadon et al ( , 2020. The generated stage-discharge function with a higher D.R.…”
Section: Figure 1 Flow Chart Of the Overall Methodologymentioning
confidence: 99%
“…The rate of riverbank erosion is significantly affected by parameters related to the pulses of water against the bank, changes in water level, the partitioning of rainfall between surface overland flows and subsurface pathways is a potentially significant driver of flood risk, as it determines the speed at which water is transferred from hillslope to the river channel (Pattison & Lane, 2012;Saadon et al, 2021).…”
Section: A Introductionmentioning
confidence: 99%