  Urban infrastructure networks play a major role in providing reliable flows
of multitude critical services demanded by citizens in modern cities. We
analyzed here a database of 125 infrastructure networks, roads (RN); urban
drainage networks (UDN); water distribution networks (WDN), in 52 global
cities, serving populations ranging from 1,000 to 9,000,000. For all
infrastructure networks, the node-degree distributions, p(k), derived using
undirected, dual-mapped graphs, fit Pareto distributions. Variance around mean
gamma reduces substantially as network size increases. Convergence of
functional topology of these urban infrastructure networks suggests that their
co-evolution results from similar generative mechanisms. Analysis of growing
UDNs over non-concurrent 40 year periods in three cities suggests the likely
generative process to be partial preferential attachment under geospatial
constraints. This finding is supported by high-variance node-degree
distributions as compared to that expected for a Poisson random graph. Directed
cascading failures, from UDNs to RNs, are investigated. Correlation of
node-degrees between spatially co-located networks are shown to be a major
factor influencing network fragmentation by node removal. Our results hold
major implications for the network design and maintenance, and for resilience
of urban communities relying on multiplex infrastructure networks for mobility
within the city, water supply, and wastewater collection and treatment.
