The Delta Connectome: A network-based framework for studying connectivity in river deltas

Abstract

Many deltas, including the Mississippi River Delta, have been losing land at fast rates compromising the safety and sustainability of their ecosystems. Knowledge of delta vulnerability has raised global concern and stimulated active interdisciplinary research as deltas are densely populated landscapes, rich in agriculture, fisheries, oil and gas, and important means for navigation.

Resilience of River Deltas in the Anthropocene

“…Whether it be modeling or observational data, the analysis strategy requires careful consideration. Processes in deltas are active over a wide range of spatial and temporal scales; couplings are usually nonlinear, thus challenging the use of classic statistical approaches such as linear correlation analyses (Passalacqua, ). Yet quantifying these couplings is fundamental to understanding how deltas respond to gradual and abrupt changes in forcing.…”

“…In the classical sense of sets of links and nodes, network representations may be too simple to capture how fluxes are transported through delta networks. Observations from the Wax Lake Delta in coastal Louisiana, for example, have shown that a large portion of the channel discharge is transferred to the island interiors via secondary channel and over levee flow (Hiatt & Passalacqua, ), thus suggesting that delta networks are leaky and the classic network model may not be always appropriate (Passalacqua, ). More complex network representations, such as a multiplex may help in this regard as they allow the representation of a system as a set of multiple networks in which links are allowed within each layer and between layers.…”

“…A first application of these tools to deltaic environments is that of Sendrowski and Passalacqua () for the analysis of water‐level fluctuations on the Wax Lake Delta in coastal Louisiana in response to wind, discharge, and tides (Figure ). The approach allows the quantification of process connectivity: viewing the variables as nodes of a network whose links are the couplings between these variables at a given scale or range of scales (Passalacqua, ). This operation is important in deltaic systems were a given change in water‐level or another variable may be caused by different factors at different scales; for example, on the Wax Lake Delta, which maintains a microtidal regime, water‐level fluctuations result from discharge, wind, and tide variability are on the order of decimeters and are often compounding, regardless of the cause (Geleynse et al, ).…”

Controllability of Surface Water Networks

“…Typically, a network is represented as a collection of nodes symbolizing junctions, inlets and outlets, and links symbolizing stream paths. Topology-based metrics have been developed to quantitatively analyze and compare surface water networks in three structurally distinct categories: (i) tributary rivers, where the flux converges from several upstream inlets to a single downstream outlet (Bertuzzo et al, 2007;Rodriguez-Iturbe & Rinaldo, 1997), (ii) braided rivers, where a single stream undergoes multiple branching/merging and eventually joins into a single stream (Foufoula-Georgiou & Sapozhnikov, 2001;Howard et al, 1970;Marra et al, 2014;Sapozhnikov & Foufoula-Georgiou, 1996, 1999, and (iii) deltas, where the flux is distributed from a single upstream inlet to several downstream outlets (Edmonds et al, 2011;Passalacqua, 2017;Smart & Moruzzi, 1971;Tejedor et al, 2015aTejedor et al, , 2015b. These studies have significantly advanced our understanding of rivers and streams as networks.…”

“…Since then, various types of networked systems such as power transmission grids (Li et al, 2016), water distribution systems (Diao & Rauch, 2013), and neuronal networks (Badhwar & Bagler, 2015, 2017 have been investigated in terms of structural controllability. Recently, Li et al (2014) provided an analytical derivation of controllability for several undirected fractal networks.…”