Enhancing Flood Resilience of Urban Drainage Networks by Identifying Blind-Spots in Logically Interconnected Systems

The growing interconnectivity of critical infrastructure systems in urban areas has escalated cascading failure risks, where disruptions in one system propagate to others. Urban drainage networks, essential for pluvial flood risk reduction, can paradoxically be vulnerable due to their interconnected network structure. While existing studies focus on physical and geographical interdependencies, the role of ‘logical interdependencies’—rooted in the numerous nested institutional policies, contingency plans, and emergency response protocols— still remains unclear. This highlights the necessity of an integrated approach that combines complex network theory and automated text analysis tools to identify hidden vulnerabilities, or "blind-spots." Logical interdependencies within urban drainage networks play a crucial role during urban flooding, where institutional gaps or human errors may inadvertently align to amplify disaster risks. To address this issue, we hypothesize that: (1) logical interdependencies can influence failure propagation, but adaptive management of blind-spots can enhance resilience; and (2) text-mining tools can effectively identify and analyze these blind-spots through institutional analysis. By adopting a multidisciplinary approach that integrates network theory and institutional analysis, this research aims to uncover critical blind-spots in logical interdependencies. The findings will provide valuable insights for enhancing sustainable stormwater management and strengthening the flood resilience of interconnected urban water infrastructure systems against coupled disaster risks.

 

Acknowledgement

This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Ministry of Science and Technology (RS-2024-00356786) and Korea Environmental Industry & Technology Institute grant funded by the Ministry of Environment (RS-2023-00218973).