Resilience of Critical Infrastructure Systems to Floods: A Coupled Probabilistic Network Flow and LISFLOOD-FP Model

Abstract

In this paper, a network-flow model was constructed to simulate the performance of interdependent critical infrastructure systems during flood hazards, when there is shortage of commodities such as electrical power and water. The model enabled us to control the distribution of commodities among different consumers whose demand cannot be fully met. Incorporating time-variance in the model allowed for evaluating the time evolution of the functional level of the infrastructure systems and quantifying their resilience. As a demonstration of the model’s capability, the network model was coupled with a raster-based hydraulic flooding model in the way of Monte Carlo simulations. It was then used to investigate the cascading effects of flood-related failures of individual infrastructure assets on the performance of the critical infrastructure systems of a coastal community under different flooding scenarios and future climate impacts. The coupled modelling framework is essential for correctly assessing the interdependences and cascading effects in the infrastructure systems in the case of flood hazards. While in the considered example, the extent of inundation becomes less severe with a changing climate, the risk to infrastructure does not recede because of the cascading effects. This behaviour could not be captured by the flood model alone.

Urban Resilience Index for Critical Infrastructure: A Scenario-Based Approach to Disaster Risk Reduction in Road Networks

“…Energy system models have been developed to simulate the production, transmission, and distribution of electricity, gas, and other forms of energy, with a focus on resilience and sustainability [29]. Water and wastewater infrastructure has been incorporated into hydrological models to assess water availability, quality, and treatment needs [39,40]. Telecommunication networks have been analyzed to understand information flow, network vulnerabilities, and the impact of disruptions on critical services [31].…”

Preparing infrastructure for surprise: fusing synthetic network, interdependency, and cascading failure models

“…In some cases, cascading failure models are often used within other models that focus on the dynamics of infrastructure interdependencies. In these cases, failure is generally not the focus but how failures affect dynamics and exchanges between the modeled networks (Holden et al 2013, Heracleous et al 2017, Wang et al 2022b, Yin et al 2022.…”

LISFLOOD-FP 8.1: New GPU accelerated solvers for faster fluvial/pluvial flood simulations

“…LISFLOOD-FP is a raster-based open-source hydrodynamic modelling framework that has been applied in many fields of 25 earth sciences, including morphodynamic modelling (Coulthard et al, 2013;Ziliani et al, 2020), urban drainage modelling (Wu et al, 2018;Yang et al, 2022), population mapping (Zhu et al, 2020), coastal flooding (Hirai and Yasuda, 2018;Seenath, 2018;Irwan et al, 2021), uncertainty quantification (Liu and Merwade, 2018;Beevers et al, 2020;Jafarzadegan et al, 2021;Karamouz and Mahani, 2021;Yin et al, 2022;Zeng et al, 2022) and coupled hydrological-hydraulic modelling (Siqueira et al, 2018;Towner et al, 2019;Hoch et al, 2019;Rajib et al, 2020;Makungu and Hughes, 2021;Nandi et al, 30 2022). It has undergone extensive developments and testing since its conception (e.g., Bates and De Roo, 2000;Hunter et al, 2005;Bates et al, 2010;Sosa et al, 2020;Shustikova et al, 2020;Zhao et al, 2020), becoming a state-of-the-art tool for flood modelling applications at urban, catchment, regional and continental scales (e.g., Amarnath et al, 2015;Chaabani et al, 2018;O'Loughlin et al, 2020;Zare et al, 2021;Bessar et al, 2021;Chone et al, 2021;Asinya et al, 2021;Zhao et al, 2021).…”