A spatial model for coastal flood susceptibility assessment using the 2D-SPR method with complex network theory: A case study of a reclamation island in Zhoushan, China

Coastal floods are the type of marine disaster that causes the greatest economic losses in coastal areas of China, especially in the current context of global climate change. Mapping the spatial distribution of coastal flood susceptibility is a prerequisite for coastal flood risk analysis, and an important step in risk prevention and management. Based on the actual coastal flood propagation process, this study uses a 2D-sour-ce-pathway-receptor (2D-SPR) model to construct a complex network for coastal flood susceptibility analysis. In addition, it uses the decision-making trial and evaluation laboratory (DEMATEL) method and the technique for order preference by similarity to an ideal solution (TOPSIS) multi-attribute decision-making method to calculate the importance of each unit in the system, namely centrality Mi which ranges from 0.0716 to 4.3524, with a higher value indicating a higher importance. Finally, the spatial distribution of coastal flood susceptibility is drawn with ArcGIS software. For a clearer display, we divide the data into 12 levels according to the natural breakpoint method, and it can be seen that coastal flood susceptibility of different regions varies greatly. The classification results have obvious regularity, overall, open-land areas or parks, waters and southeast side have relatively higher values, which belong to the higher susceptibility area among the 12 levels. From the perspective of the integrity of the geographical unit, 15 locations including unbuilt areas and water areas are identified to have high flood susceptibilities relative to the mean values of all the areas. This study fully considers the hazard formation process of coastal floods, especially the complex interaction between hazard sources and receptors. These findings provide a new perspective for the rapid, objective assessment of coastal flood susceptibility.