Developing an application within the coastal flood risk warning system: Pilot study in Quang Nam province

Flooding is one of the common natural hazards in coastal areas of Vietnam, attributed to the influence of climate change. Establishing a robust infrastructure and tools to support flood warning systems is crucial and necessary to enhance the effectiveness of early warnings. An integrated warning mechanism comprises physical components (such as sensors and computers), software applications for data processing and analysis, databases, and stakeholders including governmental agencies and local communities. Among these, community participation is a crucial aspect, aiding in the collection and dissemination of vital information for warning systems during natural disasters. Despite numerous studies focusing on developing support and warning systems for natural disasters in Vietnam, community involvement has not been sufficiently emphasized in the outcomes of these studies. This article presents the results of developing computer programs and mobile applications for flood warning services in coastal areas. Specifically, a flood risk warning map is generated using a 1D-CNN deep learning model experimented in Quang Nam province. The experimental mobile application allows community participation by enabling them to provide real-time information on the flood situation, facilitating the system's analysis, processing, updating, and integration of data into the established database to issue flood risk warnings for the research area.