Even though the impact from large tsunamis are limited to coastal areas, these events are still devastating. Knowledge is crucial in minimizing the losses from natural disasters, as it can aid in creating better and more proactive preparation. Focusing on natural hazards’ mitigation in Asia, a collaboration between 10 Asian and two European countries, based on a deeper understanding approach, has been conducted since 2015. Deeper understanding aims to discover the physical mechanisms and drivers behind a hazard event. Innovative models and simulation facilities are developed correspondingly to achieve more accurate numerical simulations of the whole lifespan of the target event. An application framework composed from the knowledge, data, simulation facility, software tools, and case studies is designed to provide an advanced estimation of hazard risk and would be evolved progressively with more case studies and observation data. For tsunamis, based on the COMCOT (COrnell Multi-grid Coupled Tsunami Model), the simulation portal (iCOMCOT) implementing parallelized tsunami wave propagation calculation over distributed clouds had been established. The iCOMCOT system finished the simulation of the whole lifecycle of the 2011 Great East Japan Earthquake Tsunami in 1 min. In this regional collaboration, case studies on historical events and tsunami impact analysis were conducted. The goal is to capture the physical characteristics of the tsunami as much as possible, such as tsunami wave propagation, tsunami refraction, and tsunami run-up on land, as well as their drivers and root causes. The whole processes of the tsunami, from its initiation to its impacts in selected locations, then could be simulated accurately by iCOMCOT based on the scientific explorations and the quantitatively revised models. The Sulawesi Tsunami (2018) case is presented to demonstrate the processes of the deeper understanding approach and how to achieve the capacity building. At the same time, ways to take advantage of citizen science are also explored. The 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 reports, and interviews from local people. According to experiences on case studies, suggestions to simplify and optimize the integration of the citizen science model with the deeper understanding approach to result in a lower operation cost are provided.