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Exploring Deltaic Network Growth and Stratigraphy Through a Rule Based Geometric Model

Abstract

We introduce a unified geometric model in which the short term fluvio-deltaic processes generating discrete sedimentary bodies and long term basin evolution coexist. Geometric aspects of delta channel networks and their long term internal stratigraphic arrangements of deltaic deposits present enormous intricacy in almost every aspect (delta shape and size, number of channels, shoreline shape, etc.). To simulate the planimetric growth of a deltaic network we employ a flexible algorithm based on a set of simple rules some of which are quantitatively anchored in physical processes while others are purely stochastic and connected to the physical process via observed field correlations among various terms (e.g., Syvitski, 2006). The model generates distributary networks in which planform of individual channels emerge from a correlated random walk algorithm through successive addition of short segments (piecewise). Each segment involves a small direction deflection, partly correlated to the previous deflection. Frequent bifurcations result in dense, anabranching channel patterns while more representative deltaic networks are obtained using a small probability bifurcation value (0.01 to 0.05). The proposed network growth model can yield distributary networks of significant morphological variation in terms of shapes, channel planforms, or channel density. The comparison between model outcomes and field analogs will be through a series of metrics such as planform shape of individual channels, delta shape, shoreline shape, or channel density distribution. Long term, a kinematic basin filling mass conservation model is used to render large scale strata arrangements which under constant sediment supply and sea level conditions consists of monotonous parallel topset and foreset packages. Varying the external forcing factors (i.e., sea level, subsidence) yields complex stratal arrangements reflecting the effects of transgression and incision. We argue that this hybrid approach driven by simple rules is suitable for investigating complex systems. By aggregating only few simple rules, due to the random terms built in, this type of model creates complex landscape patterns via randomness built in (e.g. Murray & Paola, 1994). Using simple rules also enables scenario testing and makes it easier to understand the important controls on the stratigraphic outcome.