Article

Development of flood and mudflow events for the spatio-temporal risk assessment of networks

Development of flood and mudflow events for the spatio-temporal risk assessment of networks

  • Hackl, J., Heitzler, M., Lam, J. C., Adey, B. T., and Hurni, L. (2017). Development of flood and mudflow events for the spatio-temporal risk assessment of networks. European Water, 57, 197–203. [online]

Abstract

Networks such as transport, water and power are critical lifelines to society. Network managers plan and execute interventions to guarantee their operational state under various circumstances, including after the occurrence of (natural) hazard events. Creating an intervention program demands knowing the probable network-related consequences (i.e., risk) of the various stochastic hazard events that could occur. The way such events are simulated has implications on (i) the overall computational cost of the entire risk assessment, which increases as the complexity of the network of interest increases, (ii) the accuracy of the individual risk estimations, as well as (iii) the quantified uncertainty of resulting risk estimations. To support network managers in their task to assess network-related risks, a method is presented here to develop rainfall-triggered hazard events, namely riverine flood events and mudflow events. The method enables the generation and simulation of hazard events that (i) are of a specific modeller-defined return period, enabling the characterization of the uncertainty of risk estimation for given return periods, and (ii) change over space and time, leading to the spatio-temporal estimation of network-related risk. The method is designed for network managers, and therefore, integrates computationally-efficient models that can be quickly coupled, and require data that is generally available or can be easily obtained or estimated, without impacting the integrity of the results. An example is presented to illustrate the application of the method to develop flood and mudflow events to be used in the assessment of risk for a road network in Switzerland.

Jürgen Hackl Written by:

Dr. Jürgen Hackl is an Assistant Professor at Princeton University. His research interests lie in complex urban systems and span both computational modelling and network science.