Knowledge-Building Approach for Tsunami Impact Analysis Aided by Citizen Science - Yen, Eric; Lin, Simon C.; Wu, Tso-Ren; Tsai, Yu-Lin; Chung, Meng-Ju (Frontiers in Earth Science, 2020)
Large tsunami events are devastating even though the impacts are limited to coastal areas. Knowledge is the key to minimize the losses from natural disasters by more proactive and better preparation. Targeting on natural hazards mitigation in Asia, a collaboration among 10 Asian and 2 European countries based on deeper understanding approach has been conducted since 2015. Deeper understanding is to discover the physical mechanisms and drivers behind a hazard event. Innovative model and simulation facilities are developed correspondingly to achieve more accurate numerical simulations of the whole lifespan of the target event. Application framework composed by the knowledge, data, simulation facility, software tools and case studies is designed to provide advanced estimation of hazard risk and would be evolved progressively with more case studies and observation data. For tsunami, based on the COMCOT (COrnell Multi-grid Coupled Tsunami Model), the simulation portal (iCOMCOT) implementing parallelized tsunami wave propagation calculation over distributed cloud had been established. iCOMCOT system finished the simulation of whole lifecycle of the 2011 Great East Japan Earthquake Tsunami in one minute. In this regional collaboration, case studies on historical events and tsunami impact analysis were conducted. The goal is to capture the physical characteristics of tsunami as much as possible such as tsunami wave propagation, tsunami refraction, tsunami run-up on land, as well as their drivers and root causes. The whole processes of tsunami from its initiation to its impacts in selected locations then could be simulated accurately by iCOMCOT based on the scientific explorations and the revised models quantitatively. Sulawesi Tsunami (2018) case is presented to demonstrate the processes of deeper understanding approach and how to achieve the capacity building. At the same time, the ways to take advantages of citizen science are also explored. Citizen science model is valuable in supporting data collection such as data of run up height, inundation range, flow depth, disruption information, impact area, from publication, news report, and interviews of local people. According to experiences on case studies, suggestions to simplify and optimize the integration of citizen science model with deeper understanding approach to lower operation cost are provided.