Quantifying the signature of sediment composition on the topologic and dynamic complexity of river delta channel networks and inferences toward delta classification

Deltas contain complex self‐organizing channel networks that nourish the surface with sediment and nutrients. Developing a quantitative understanding of how controlling physical mechanisms of delta formation relate to the channel networks they imprint on the landscape remains an open problem, hinder...

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Bibliographic Details
Published in:Geophysical research letters 2016-04, Vol.43 (7), p.3280-3287
Main Authors: Tejedor, Alejandro, Longjas, Anthony, Caldwell, Rebecca, Edmonds, Douglas A., Zaliapin, Ilya, Foufoula‐Georgiou, Efi
Format: Article
Language:English
Subjects:
Brackish
channel networks
Channels
Classification
Classification (sedimentation)
Complexity
delta
delta classification
Deltas
Freshwater
graph theory
Inference
Networks
Rivers
sediment
Sediment composition
Sediments
Steady state
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Summary:Deltas contain complex self‐organizing channel networks that nourish the surface with sediment and nutrients. Developing a quantitative understanding of how controlling physical mechanisms of delta formation relate to the channel networks they imprint on the landscape remains an open problem, hindering further progress on quantitative delta classification and understanding process from form. Here we isolate the effect of sediment composition on network structure by analyzing Delft3D river‐dominated deltas within the recently introduced graph‐theoretic framework for quantifying complexity of delta channel networks. We demonstrate that deltas with coarser incoming sediment tend to be more complex topologically (increased number of pathways) but simpler dynamically (reduced flux exchange between subnetworks) and that once a morphodynamic steady state is reached, complexity also achieves a steady state. By positioning simulated deltas on the so‐called TopoDynamic complexity space and comparing with field deltas, we propose a quantitative framework for exploring complexity toward systematic inference and classification. Key Points Sediment composition leaves a distinct signature on delta channel network complexity As deltas evolve and reach steady state, complexity also achieves steady state A TopoDynamic complexity space offers potential for process inference and delta classification
ISSN:0094-8276
1944-8007
DOI:10.1002/2016GL068210