Assessing Erosion Hazards due to Floods on Fans: Physical Modeling and Application to Engineering Challenges

Eaton, Brett C.; MacKenzie, Lucy G.; Jakob, Matthias; Weatherly, Hamish

doi:10.1061/(asce)hy.1943-7900.0001318

Cited by 11 publications

(11 citation statements)

References 45 publications

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“…If the bank erosion threshold is exceeded, a new channel width is calculated. Consistent with experimental evidence (Eaton et al, ; Pitlick et al, ), the size of the new channel adjusts to the imposed flood magnitude; erosion progresses until the reach‐averaged boundary shear stress is reduced to the threshold value. Flume experiments conducted by Pitlick et al () and Eaton et al () show that this erosion can occur rapidly (within a single day of flow in a prototype system) as eroded material deposits in the center of the channel leading to sedimentation of the channel bed.…”

Section: Model Descriptionsupporting

confidence: 73%

“…Consistent with experimental evidence (Eaton et al, ; Pitlick et al, ), the size of the new channel adjusts to the imposed flood magnitude; erosion progresses until the reach‐averaged boundary shear stress is reduced to the threshold value. Flume experiments conducted by Pitlick et al () and Eaton et al () show that this erosion can occur rapidly (within a single day of flow in a prototype system) as eroded material deposits in the center of the channel leading to sedimentation of the channel bed. However, while this may be typical of systems with easily erodible bank material and relatively long duration flow events (e.g., nival hydroclimates), flood duration may affect the extent of widening (and the capacity for morphologic adjustment) in arid systems subject to short‐duration, flashy high flow events.…”

Section: Model Descriptionsupporting

confidence: 73%

“…During the flood the reach widens if the shear stress associated with the flood event exceeds a bank erosion threshold ( τ bank ). Based on experimental evidence, we define this threshold as the critical shear stress associated with full mobility of the coarse fraction ( D 84 ) of the bed material (Eaton et al, ; MacKenzie & Eaton, ). We assume that all predicted erosion can be accomplished during the 24‐hr flood duration and that no erosion occurs throughout the rest of the year.…”

Section: Model Descriptionmentioning

confidence: 99%

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Beyond Regime: A Stochastic Model of Floods, Bank Erosion, and Channel Migration

Davidson

Eaton

2018

Water Resources Research

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Equilibrium or regime models based on a single formative (channel‐forming) discharge have been instrumental in developing a quantitative understanding of river channel dynamics. However, alternative paradigms can be used to ask fundamentally different questions about river channel behavior. In this paper, we present the Stochastic Channel Simulator (STOCHASIM), a simple biogeomorphic model that models the interplay between erosion and vegetation encroachment through changes in channel geometry. Results for a range of flood distributions are compared to predictions from a similar model based upon a traditional regime approach. Flood variability strongly influences the mean channel geometry and channel stability; the regime model and the stochastic model predict the same channel width when flow variability is low but diverge as flow variability increases. The return period of the formative flow required to match the geometry generated by a traditional regime approach increases systematically, from about 2 years for flow regimes in humid regions to nearly 8 years for more variable flow regimes, like those typical of arid regions. While the traditional regime approach provides a reasonable simplification for streams with little variability in the flood distribution, stochastic modeling may provide more realistic estimates of channel size as flood variability increases (e.g., in arid streams or small watersheds). The success of STOCHASIM in replicating realistic patterns of erosion, as well as the historical contingency often observed in natural streams, suggests that adopting a stochastic dynamics paradigm could advance geomorphology, just as it has done in hydrology, ecology, and other natural sciences.

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Section: Model Descriptionsupporting

confidence: 73%

Section: Model Descriptionsupporting

confidence: 73%

Section: Model Descriptionmentioning

confidence: 99%

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Beyond Regime: A Stochastic Model of Floods, Bank Erosion, and Channel Migration

Davidson

Eaton

2018

Water Resources Research

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“…Furthermore, given changes in bed stability in response to interflood flow duration are grade sensitive our results indicate the not only is predicting entrainment based on a single critical Shield's value inaccurate but also that the D 50 may not be the best grain fraction from which to estimate entrainment thresholds (MacKenzie et al, 2018). This study has shown that the finest and coarsest fractions are most responsive to inter-flood flow duration and hence more realistic entrainment models might consider using these fractions to define bed stability (Carling, 1987(Carling, , 1988Ashworth and Ferguson, 1989;Eaton and Church, 2004;Tamminga et al, 2015;Eaton et al, 2017;MacKenzie and Eaton, 2017).…”

Section: Discussionmentioning

confidence: 90%

“…However, as supported by Piedra and Haynes (2011) data in this article also indicates that there is no unique equation with fixed parameters capable of describing bedload transport behaviour for gravel channels which have been exposed to differing inter-flood flow periods. This study has shown that the finest and coarsest fractions are most responsive to inter-flood flow duration and hence more realistic entrainment models might consider using these fractions to define bed stability (Carling, 1987(Carling, , 1988Ashworth and Ferguson, 1989;Eaton and Church, 2004;Tamminga et al, 2015;Eaton et al, 2017;MacKenzie and Eaton, 2017). This study has shown that the finest and coarsest fractions are most responsive to inter-flood flow duration and hence more realistic entrainment models might consider using these fractions to define bed stability (Carling, 1987(Carling, , 1988Ashworth and Ferguson, 1989;Eaton and Church, 2004;Tamminga et al, 2015;Eaton et al, 2017;MacKenzie and Eaton, 2017).…”

Section: Effect Of Inter-flood Duration On Bed Stabilitymentioning

confidence: 97%

The impact of inter‐flood duration on non‐cohesive sediment bed stability

Ockelford

Woodcock

Haynes

2019

Earth Surf Processes Landf

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Limited field and flume data suggests that both uniform and graded beds appear to progressively stabilize when subjected to inter‐flood flows as characterized by the absence of active bedload transport. Previous work has shown that the degree of bed stabilization scales with duration of inter‐flood flow, however, the sensitivity of this response to bed surface grain size distribution has not been explored. This article presents the first detailed comparison of the dependence of graded bed stability on inter‐flood flow duration. Sixty discrete experiments, including repetitions, were undertaken using three grain size distributions of identical D50 (4.8 mm); near‐uniform (σg = 1.13), unimodal (σg = 1.63) and bimodal (σg = 2.08). Each bed was conditioned for between 0 (benchmark) and 960 minutes by an antecedent shear stress below the entrainment threshold of the bed (τ*c50). The degree of bed stabilization was determined by measuring changes to critical entrainment thresholds and bedload flux characteristics. Results show that (i) increasing inter‐flood duration from 0 to 960 minutes increases the average threshold shear stress of the D50 by up to 18%; (ii) bedload transport rates were reduced by up to 90% as inter‐flood duration increased from 0 to 960 minutes; (iii) the rate of response to changes in inter‐flood duration in both critical shear stress and bedload transport rate is non‐linear and is inversely proportional to antecedent duration; (iv) there is a grade dependent response to changes in critical shear stress where the magnitude of response in uniform beds is up to twice that of the graded beds; and (v) there is a grade dependent response to changes in bedload transport rate where the bimodal bed is most responsive in terms of the magnitude of change. These advances underpin the development of more accurate predictions of both entrainment thresholds and bedload flux timing and magnitude, as well as having implications for the management of environmental flow design. © 2019 John Wiley & Sons, Ltd. © 2019 John Wiley & Sons, Ltd.

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Breaking from the average: Why large grains matter in gravel‐bed streams

MacKenzie

Eaton

Church

2018

Earth Surf Processes Landf

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While the influence of large grains on the morphodynamics of gravel‐bed rivers has long been recognized, nothing dominates our collective efforts to model such rivers like the bed surface D50, which turns up in virtually all the relevant equations. While researchers interested in flow resistance have recognized the relative importance of large grains and have modified flow resistance equations accordingly, there have been few attempts to quantify the effects of large grains on gravel‐bed river morphodynamics. However, there is little evidence that D50 exerts first‐order control over the physics occurring along the channel boundary, and its prevalence seems to be primarily based on the untested, a priori assumption that the best description of a distribution is the mean or median value. This commentary questions the long‐standing assumption that D50 is the best choice for characteristic grain size, and uses evidence from previous studies to show that mobilization of the largest grains in the bed likely controls morphological stability, and possibly sediment transport. © 2018 John Wiley & Sons, Ltd.

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Assessing Erosion Hazards due to Floods on Fans: Physical Modeling and Application to Engineering Challenges

Cited by 11 publications

References 45 publications

Beyond Regime: A Stochastic Model of Floods, Bank Erosion, and Channel Migration

Beyond Regime: A Stochastic Model of Floods, Bank Erosion, and Channel Migration

The impact of inter‐flood duration on non‐cohesive sediment bed stability

Breaking from the average: Why large grains matter in gravel‐bed streams

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