Network Modeling and Dynamic Mechanisms of Multi-Hazards—A Case Study of Typhoon Mangkhut

Abstract

Coastal areas are home to billions of people and assets that are prone to natural disasters and climate change. In this study, we established a disaster network to assess the multi-hazards (gale and heavy rain) of typhoon disasters, specifically Typhoon Mangkhut of 2018 in coastal China, by applying the methodology of a bipartite network in both time dimension and spatial dimension. In this network, the edge set and adjacent matrix are based on the connection between an hour and a city with a multi-hazards impact that includes gales and heavy rain. We analyze the characteristics and structure of this disaster network and assess the multi-hazards that arose from Typhoon Mangkhut in different areas. The result shows that there are 14 cities in the core area and 21 cities in the periphery area, based on core–periphery classification in the disaster network. Although more damage area belongs to the periphery area, the percentage of the population affected by the typhoon and direct economic loss in GDP in the core area was 69.68% and 0.22% respectively, which is much higher than in the periphery area (55.58% and 0.06%, respectively) The core area suffered more from multi-hazards and had more disaster loss. This study shows that it is feasible to assess multiple hazards with a disaster network based on the bipartite network.