Table 2.

Flow properties (A), reach properties, climate and flood hazard (B), morphodynamics properties (C) and scale-dependent parameters (D) presents present different roles in the network (most important roles highlighted in bold). Clusters with higher betweenness centrality (C) have more control over the network, because more information pass through their nodes. Their role is related to the network’s connectivity, in so much as high betweenness vertices have the potential to disconnect graphs if removed. Assuming that vertices can only pass messages to or influence their existing connections, a clusters with low closeness centrality (B) means that are directly connected or “just a hop away” from most others in the network. In contrast, clusters in very peripheral locations may have high closeness centrality scores (D), indicating the high number of hops or connections they need to take to connect to distant others in the network. Degree centrality shows how many connections a cluster has. They may be connected to lots of nodes at the heart of the network (D), but they might also be far off on the edge of the network. Clusters with high strength (B) present connections with a higher level of correlation.

	A	B	C	D
	flow properties	reach properties, climate and flood hazard	morphodynamics properties	scale-dependent parameters
betweenness	0.250	0.176	0.411	0.257
closeness	0.532	0.358	0.615	0.821
degree	0.438	0.571	0.550	0.786
strength	0.348	0.589	0.415	0.525