Flood hazards affect the local economy and the livelihood of residents along the South-Central Coast of Vietnam. Understanding the factors influencing floods’ occurrence potentially contributes to establish mitigation responses to the hazards. This paper deals with an empirical study on applying a combination of the fuzzy analytic hierarchy process (AHP), the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS), and a geographic information system (GIS) to assess flood hazards along the South-Central Coast of Vietnam. Data are collected from focus group discussions (FGDs) with five communal authorities; a questionnaire completed by eight hamlet heads in the Phuoc Thang commune (Binh Dinh province); and documents, reports, and thematic maps provided from official sources. A total of 12 maps of flood factors are prepared. The results show that terrain elevation, creek-bottom terrains, high tide-induced flooding area, and distance to water body are the main factors affecting flood hazards. The An Loi hamlet faces the highest risk for floods, followed by Lac Dien, Luong Binh, and Pho Dong. The map of flood hazards indicates the western part is assessed as low hazard, whereas the eastern part is a very high hazard area. The study findings show that the hybrid approach using GIS-based fuzzy AHP–TOPSIS allows connecting decision makers with the influencing factors of flooding. To mitigate floods, both the Vietnam national government and the Binh Dinh provincial government should integrate natural hazard mitigation into socio-economic development policies.

In recent years, Vietnam’s South-Central Coast has experienced increasingly severe flooding due to heavy rainfall and tropical depressions. This has led to widespread inundation in the downstream areas of the Kon and Ky Lo river basins, causing significant property damage and loss of life. This study aims to develop historical flood and hazard maps to assess flood severity and estimate potential damage. Using Google Earth Engine, flood extents for the 2016 and 2021 flood events were extracted based on object reflectance thresholds and validated against historical flood records, ensuring high accuracy. The findings indicate that in 2016, the Kon River Basin experienced more extensive flooding, whereas in 2021, the Ky Lo River Basin was more severely affected. By classifying flood hazard zones based on depth, the study found that high-hazard areas accounted for over 25% of the total basin area. These insights provide valuable guidance for local authorities in enhancing flood mitigation efforts, land-use planning, and disaster response strategies to improve resilience and minimize future flood-related losses.