2017
DOI: 10.1002/2015jf003778
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Morphodynamic modeling of fluvial channel fill and avulsion time scales during early Holocene transgression, as substantiated by the incised valley stratigraphy of the Trinity River, Texas

Abstract: The Trinity River system provides a natural laboratory for linking fluvial morphodynamics to stratigraphy produced by sea-level rise, because the sediments occupying the Trinity incised valley are well constrained in terms of timing of deposition and facies distribution. Herein, the Trinity River is modeled for a range of base-level rise rates, avulsion thresholds, and water discharges to explore the effects of backwater-induced in-channel sedimentation on channel avulsion. The findings are compared to observe… Show more

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Cited by 25 publications
(50 citation statements)
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References 41 publications
(126 reference statements)
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“…In contrast, constant discharge numerical experiments tend toward a graded state without strong backwater effects or a preferential node location. Our results suggest that previous numerical models that lacked variable discharges and produced backwater‐scaled avulsions (Moran et al, ; Ratliff, ) were likely affected by initial conditions of uniformly sloped initial surfaces. A backwater‐scaled avulsion node under these conditions is a geometric consequence of assessing superelevation of a prograding channel or lobe relative to a planar seaward sloping landscape.…”
Section: Discussionmentioning
confidence: 98%
See 1 more Smart Citation
“…In contrast, constant discharge numerical experiments tend toward a graded state without strong backwater effects or a preferential node location. Our results suggest that previous numerical models that lacked variable discharges and produced backwater‐scaled avulsions (Moran et al, ; Ratliff, ) were likely affected by initial conditions of uniformly sloped initial surfaces. A backwater‐scaled avulsion node under these conditions is a geometric consequence of assessing superelevation of a prograding channel or lobe relative to a planar seaward sloping landscape.…”
Section: Discussionmentioning
confidence: 98%
“…In particular, the model of Chatanantavet et al (2012) requires flow variability to produce a persistent avulsion node, consistent with available experimental data, but the elimination of river mouth progradation in their model might have biased their results. In contrast, more recent models (Moran et al, 2017;Ratliff, 2017) can produce persistent avulsion nodes with constant discharge, but they impose an unrealistic initial condition. To address these potentially problematic assumptions, we constructed a quasi-2-D numerical model that allows for repeated lobe construction and avulsion such that lobes build on top of one another, thereby minimizing the role of initial topography as the delta evolves.…”
Section: 1029/2019gl082491mentioning
confidence: 99%
“…This work explored how backwater and base‐level adjustments combine to influence sediment deposition patterns. Moran, Nittrouer, Perillo, Lorenzo‐Trueba, and Anderson () developed a morphodynamic model for the Trinity River (Texas) by considering Holocene sea‐level rise. This work documents a consistent back‐stepping of the backwater zone, accompanied by bed material sediment filling of the Trinity River incised valley.…”
Section: Background: Nonuniform Flow In Sedimentary Dispersal Systemsmentioning
confidence: 99%
“…Since the 1D model is width‐averaged and width changes in the along‐stream direction for the channel and floodplain is not considered, the inclusion of normalΛ, normalΩ, If and rB in the model helps to account for deposition in floodplain and flood intermittency of natural rivers so that the model simulation has application to real rivers (Parker, ). Short of measuring these parameters from field data, standard values from modern lowland systems that scale with the ancient basins are utilized (Table ) (Moran et al, ; Parker et al, ). The channel bed profile evolves iteratively with each time step by solving Equations (1)–(3), over the horizontal distance ( x ).…”
Section: Analytical Frameworkmentioning
confidence: 99%
“…where H bf is a characteristic channel bankfull flow depth and is a coefficient that varies between 0.3 and 1 on modern delta systems but may be >1 for fan-delta systems (Ashworth et al, 2004;Bryant et al, 1995;Ganti et al, 2014Ganti et al, , 2016aGanti et al, , 2016bJain & Sinha, 2004;Jerolmack & Mohrig, 2007;Heller & Paola, 1996;Martin et al, 2009;Moran et al, 2017;Mohrig et al, 2000;Stouthamer & Berendsen, 2001;Törnqvist, 1994). Ganti et al, 2014, after Pang & Si, 1979van Gelder et al, 1994).…”
Section: Introductionmentioning
confidence: 99%