The significance of critical infrastructure systems in maintaining productivity is undeniable. However, such systems remain susceptible to external disturbances and cascading failures. Instead of operating independently, these physical systems, such as transportation and stormwater systems, form an interdependent system. This interdependence, particularly important during flooding, illustrates that the failure of a stormwater system can disrupt traffic networks. To explore the extent of such interdependency, this study investigates the transportation and stormwater networks in Norman, Oklahoma. Using network science theories and concepts of multilayered networks, this paper analyzes these systems, both individually and in combination. The study identifies closely located components in the road and stormwater networks using Moran's I spatial autocorrelation metric. Next, the connectivity of these networks is represented in a graph format to investigate the topological credentials (i.e., rank of relative importance) of the network components (i.e., water inlets, road intersections as nodes, and stormwater conduits, road segments as links). Moreover, such credentials further change by considering the weights of the network components (i.e., average daily traffic, water flow). The proximity-based connectivity considerations between these networks utilizing Moran's I significance score revealed a good indicator of spatial interdependency. When incorporating directionality, the multilayer network analysis highlights that highly central components tend to cluster spatially, unlike the undirected counterpart. The study also identifies vulnerable locations and network components in a combined network setting that differ from the networks in isolation. In doing so, the research reveals new insights governing the complex reliance of transportation systems on neighboring stormwater systems.
Failures within water distribution systems are usually not isolated and tend to propagate to corresponding transportation infrastructure, yet most criticality and resilience analyses of water distribution networks are conducted for the individual water infrastructure without accounting for interdependence. To address this research gap, this study investigates how the critical components identified within water distribution systems may be different when accounting for failure propagation to the transportation road network. In this study, failure propagation is assumed to be based on geospatial interdependence and unidirectional, starting from water distribution network components to transportation network components. A logical interaction network is constructed considering the interdependence between both infrastructures, and multiobjective optimization is used to solve for the critical water distribution components considering: quantity of failures, performance loss, and financial costs. This work presents a modular workflow for water distribution criticality analysis and proposes the Kolmogorov‐Smirnov distance statistic between solution sets as a measure of the significance of interdependency for decision making. Results from the case study suggest that as the magnitude of water infrastructure failure increases beyond a threshold, the interdependency between water distribution and transportation becomes more significant. The difference between identified critical components using only information from water distribution and using both water distribution and transportation is significantly different (with greater than 95% confidence) for the city of Tampa, when more than 40 components fail (are isolated). These results will assist utilities in asset management and strategy assessment, by helping prioritize component repair and better allocate resources for critical interdependent infrastructures.
more » « less- Award ID(s):
- 1638301
- NSF-PAR ID:
- 10456283
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Water Resources Research
- Volume:
- 55
- Issue:
- 7
- ISSN:
- 0043-1397
- Page Range / eLocation ID:
- p. 5255-5276
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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