An Event-Driven, Scalable and Real-Time Geo-spatial Disaster Forensics Architecture: Decision Support for Integrated Disaster Risk Reduction

“An event-driven, scalable and real-time, geo-spatial disaster forensics architecture” uses advances in decision support systems to apply forensic theory, insight and analysis to disaster related research and practice. It examines water resources disasters and their impact on humans, the built environment and natural systems. The chapter also identifies, and describes timely and innovative decision support architectures to analyze climate related disasters, enhance emergency preparedness, reduce disaster risk, promote disaster resilience and improve disaster mitigation, adaption, and management. The root causes of water resources disasters are explored and a distributed, scalable and real-time disaster forensics architecture with event-driven messaging and advanced geomatics engineering capabilities is put forth. Emphasis is given to vigilant monitoring, assessment, response and recovery of floods and oil and molasses spills in the US state of Hawaii. The decision support and situational awareness advances found in this chapter complement the recent success of water resources disaster risk management and disaster forensics in Europe and elsewhere. The herein proposed disaster forensics architecture helps managers uncover creative, timely and important strategies for analyzing water resources accidents and disasters. In this manner, professionals have additional tools to model the complex causality of disasters and are better equipped to apply disaster forensics theory to the promotion of a more holistic, sustainable relationship between society and the environment. Specifically, this contribution provides theoretical insights and practical examples to manage water resources disasters under uncertainty.

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