A topological characterization of flooding impacts on the Zurich road network

Abstract

Infrastructure systems are the structural backbone of cities, facilitating the flow of essential services. Because those systems can be disrupted by natural hazards, risk management has been the prevailing approach for assessing the consequences and expected level of damage. Although this may be a valuable metric, the practice of risk assessment does not represent how hazards affect a network of assets on a larger scale. In contrast, network topology metrics are useful because they evaluate the performance of network infrastructures by looking at the system as a whole. As described here, we began this study to improve our understanding of how flooding events affect the topological properties of road networks, in this case, the urban road infrastructure of Zurich, Switzerland. Using maps of flooding risk, we developed a procedure to extract the damaged networks and analyze the centrality metrics for peak water levels on the surface of the city. Our approach modelled roads as edges and junctions between roads as nodes. The betweenness centrality metric characterizes the importance of nodes or edges for any type of exchange within a network, whereas the closeness centrality metric measures the accessibility of a specific node to all the other nodes. This investigation produced three main findings. First, descriptive analyses showed that the characteristics and patterns of nodes and edges changed under the flooding events. Second, the distribution function of centrality metrics became heavier in the tails as the flood magnitude increased. Third, the associated strain shifted critical nodes to areas in which those nodes would not be important under normal conditions. These findings are essential for identifying crucial locations and devising plans to address risks. Future projects could expand our approach by including traffic flow to move the analysis closer to real-world flows, and by studying the accessibility under emergency conditions at local levels.

Indirect flood impacts and cascade risk across interdependent linear infrastructures

“…These models simulate pressure behaviour in the nodes of the network if components supplied by electricity are affected by flooding (Arrighi et al, 2017;Tarani et al, 2019); pressure fluctuations or low pressures may lead to contamination from leakage orifices and air vacuum valves (Ebacher et al, 2010;Ellison et al, 2003). Existing works implemented methods which integrate geographic information system (GIS) analysis, inundation modelling and hydraulic network modelling with pressure-driven demand (PDD) (Cheung et al, 2005;Siew and Tanyimboh, 2012;Tarani et al, 2019). Two metrics measure flood impact to the WSS operativeness and integrity: (i) the number of inhabitants experiencing lack of service and (ii) the total length of potentially contaminated pipes (Arrighi et al, 2017).…”

“…In the context of flooded roads, impact assessment criteria include the (i) number of flooded links, (ii) timing (flood duration, operation time, traffic dynamics) and (iii) level of performance (e.g. speed reduction, road capacity reduction) (Casali and Heinimann, 2019;Kermanshah and Derrible, 2017;Balijepalli and Oppong, 2014). Available silo-based studies investigated road links' vulnerability and their failure impact on the overall network functioning (that is crucial for emergency planning); however, they ignore the impact of disconnection and lack of accessibility to critical services, which lead to cascading effects.…”

Assessing the effects of link-repair sequences on road network resilience

“…It is noted that localised disruptions are normally specified in terms of hazard-prone areas derived from climate models (Casali and Heinimann, 2019;Demirel et al, 2015;Hu et al, 2016;Wisetjindawat et al, 2017). In this model, localised failures refer to a range of events that may differ in nature (flooding, landslide, or large demonstrations) but lead to similar consequences, that is, the unavailability of adjacent network components.…”

Flood impact on urban roads and commuting: A case study of Wuhan, China

“…According to different research interests of the research field, the value dimensions of performance indicators to reveal road vulnerability are different (Jenelius et al, 2006;Balijepalli and Oppong, 2014;El-Rashidy and Grant-Muller, 2014;Mattsson and Jenelius, 2015). Many scholars in the field of transportation networks focused on measuring the impact of local road failure on the overall road network system from a global perspective (Demirel et al, 2015;Casali and Heinimann, 2019). Scholars who focus on spatial justice tend to reveal local road damage in spatial units or at the scale of road sections (Liu et al, 2021).…”