Resilience in urban networked infrastructure: the case of Water Distribution Systems

TL;DR

This paper explores how spectral analysis and clustering techniques from network theory can assess and enhance the resilience of water distribution systems by identifying critical components and global connectivity measures.

Contribution

It introduces a novel approach combining spectral analysis and clustering to evaluate and improve resilience in water distribution networks.

Findings

Spectral analysis provides a mathematically sound measure of global connectivity.

Clustering identifies critical edges whose failure impacts network integrity.

Method applicable to generic networked infrastructures, with focus on water systems.

Abstract

Resilience is meant as the capability of a networked infrastructure to provide its service even if some components fail: in this paper we focus on how resilience depends both on net-wide measures of connectivity and the role of a single component. This paper has two objectives: first to show how a set of global measures can be obtained using techniques from network theory, in particular how the spectral analysis of the adjacency and Laplacian matrices and a similarity measure based on Jensen-Shannon divergence allows us to obtain a characteriza-tion of global connectivity which is both mathematically sound and operational. Second, how a clustering method in the subspace spanned by the l smallest eigen-vectors of the Laplacian matrix allows us to identify the edges of the network whose failure breaks down the network. Even if most of the analysis can be applied to a generic networked infrastructure, specific references will be made to Water Distribution Networks (WDN).