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ADAPTIVE DECISION SUPPORT SYSTEM TO NAVIGATE THE COMPLEXITY OF POST-DISASTER DEBRIS MANAGEMENT
thesisposted on 05.11.2019, 20:45 by Jooho KimJooho Kim
Disaster debris management is critical to the success of disaster recovery systems. While there are multiple disaster mitigation strategies and post-disaster debris management plans, it is hard to implement because of: (i) the uniqueness of disaster incidents and randomness of its impacts; (ii) complexity of disaster debris removal operations, policy and regulations and (iii) interdependency of multiple infrastructure networks. Also, delayed debris removal operation affects following emergency response activities. Furthermore, uncontrolled debris removal activities can result in significant environmental and public health consequences. Therefore, there is a need for a systematic approach to optimizing post-disaster debris management systems.
This research is aimed to understand the complexity of debris management and associated emergent dynamics through the lens of an adaptive system-of-systems (SoS). To develop the adaptive decision support system, this research (a) identifies the interdependent infrastructure network within a community and its relative importance; (b) develops real-time GIS database to integrate the data associated with critical infrastructure and geographical characteristics in the community map; (c) designs and selects a TDMS network to analyze the required number, capacity and resources, based on engineering-technical, managerial, and social-political dynamics; (d) simulate the productivity of debris-management SoS based on the real-time GIS database to gain insight into the impact of the dynamical nature of a disaster-affected area; and (e) develop a visualized interactive GIS-based platform for debris management to communicate real-time debris clearance strategies and operations among different agencies and organizations.
To evaluate the proposed framework and decision support system, this research conducted a case study, debris removal operation in the city of Baton Rouge, after the 2016 Louisiana flood. The results demonstrated the influence of sub-systems such as TDMS locations and capacity, road network condition, available resources, existing regulations and policies, characteristics of community on the behavior of the entire disaster debris removal management as a whole.
The proposed decision support system for effective disaster debris management will be beneficial for emergency agencies and disaster-prone communities to evaluate and optimize their disaster debris management system. Also, the system can be systematically integrated with other emergency response systems to maximize the efficiency of the entire disaster responses during post-disaster situations.