Flood Resilience Assessment for Flood Defense Infrastructures
[Research Overview]
The intensifying impact of climate change has led to more frequent flooding, escalating the scale of human and economic losses in urban environments. While flood defense infrastructure is currently in operation to minimize these damages, it primarily relies on reactive measures based on historical rainfall data. This traditional approach is becoming increasingly insufficient for addressing the unpredictable nature of future climate patterns.
To overcome these limitations, the Resilient Infrastructure Lab (RIL) aims to establish a proactive framework by introducing the concept of "Resilience"—encompassing prevention, absorption, recovery, adaptation, and transformation—into infrastructure management systems.
Defining resilience as the "capacity of a system to maintain and recover its performance against external disturbances," we are conducting research to concretize complex evaluation metrics. Our ultimate goal is to build a robust assessment and management system for flood defense capable of withstanding extreme flood events driven by climate change.
[Key Research Areas]
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Investigation of Damage Factors: Analyzing failure factors and case studies of flood defense infrastructure.
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Resilient Behavior Analysis: Analyzing the disaster-prevention behaviors of infrastructure under flood conditions.
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Indicator Development: Developing comprehensive resilience assessment indicators for flood defense systems.
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Prediction & Policy: Predicting infrastructure resilience for climate adaptation and deriving strategies for policy improvement.
Resilience of Ecological Network in Wetlandscape
Wetlands distributed in a large landscape play a critical role in providing various ecosystem services including the provision of ecological habitats, hydrologic controls, and biogeochemical processes. These services are, however, also controlled by hydro-climatic and geological conditions and dispersal pattern of inhabiting species. We are interested in various dispersal models to allow dispersal strategies between habitats. Implications of modeling ecological networks will provide a new decision-making process, especially for conservation purposes.
Generating ecological networks using dispersal models (Left: threshold; middle: exponential kernel; right: heavy-tailed model)
Topological analysis of urban water network
For the provision of a reliable supply of water services, water distribution network should be designed and managed to cope with various threats (e.g., disasters). Due to physical properties of this kind of infrastructure, we can view it as a network (or graph) to apply complex system network theory. However, a primal network has limitations to analyze network topology because of spatial features of the network. We aim to develop a dual method to enable getting a deeper insight and more meaningful analytical results from this network. This newly obtained information will be helpful for improving the resilience of infrastructures as complex networks.
Fig 1. Analysis of water distribution network topology, Geojedo Island, South Korea.
Fig 2. Water distribution system, Jeon-ju city, South Korea.
Water Cycle Sustainability in Megacities
Many cities are facing various water-related challenges caused by rapid urbanization and climate change. Moreover, a megacity may pose a greater risk due to its scale and complexity for coping with impending challenges. Thus, it is important to diagnose key barriers and opportunities in a city's environmetal surroundings, infrastructures, and governance regarding water management to enable building a resilient urban society. By adopting the City Blueprint® Approach, we try to assess the various aspects that govern the water cycle of a city. Based on the assessment, we also try to propose priority of specific strategies that should be applied for improving urban water resilience.
City Blueprint Approach
(Source: https://www.eip-water.eu/City_Blueprints)
Topology and Resilience of Socio-technical Networks
We are interested in topology and its relation to the resilience of various networked infrastructures such as power grids. As a case study, we have analyzed Korean power grid (KPG) providing another empirical evidence of power grid topology. We identify node degree distribution, efficiency and clustering coefficient, etc. We also do the analysis to test error and attack tolerance of the networks using various scenarios (e.g., intentional vs. random attacks, cascading failures).
For more details, see our recent publication in Physica A
In addition to viewing infrastructure as a solely technicial network, we view it as an engineered complex system coupled by social and technical system. The logic underlying this is by recognizing how well a system recovers from failures depends on policies and protocols for human and organizational coordination that must be considered alongside technological analyses.
Here is our another recent publication in COMPEXITY.
Map of Korean power grid
(Source: Eisenberg et al. 2018)