Coastal flood sensitivity assessment method

Abstract

The invention relates to the technical field of flood disaster assessment information processing methods, in particular to a coast flood sensitivity assessment method, which combines an actual coast flood transmission process and utilizes a 2D-SPR model framework to construct a complex network for coast flood sensitivity analysis. And drawing a spatial distribution diagram of the coast flood sensitivity by utilizing a DEMATEL method and a TOPSIS multi-attribute decision-making method in combination with an ArcGIS platform, and confirming an area with relatively high flood sensitivity. According to the method, the areas affected by different degrees of flood in the area can be visually, rapidly and efficiently determined, corresponding retarding measures are made on the basis, and rapid and subjective interference-free coast flood sensitivity evaluation is realized.

Description

technical field [0001] The invention relates to the technical field of flood disaster assessment information processing methods, in particular to a coastal flood disaster sensitivity assessment method. Background technique [0002] Frequent extreme weather events and long-term climate change have led to a continuous increase in the frequency of natural disasters. Among them, floods are considered to be one of the most destructive natural disasters with the highest economic losses, and the number of occurrences has even reached 34%. Coastal areas with high human activity face a greater threat of flooding than other regions, a trend exacerbated by rising sea levels and potential changes in storm surges. The study believes that the social and economic agglomeration effect of coastal areas is the main reason for the continuous increase of flood losses. [0003] The coastal area only accounts for 13% of my country's land area, but has 43.5% of the country's population and 60.8% ...

AI Technical Summary

Problems solved by technology

At present, researchers have made a lot of achievements in this field. The methods used mainly include: 1) Statistical analysis method based on historical data. This method is mainly based on actual field survey data and requires relatively large costs, but the results are not satisfactory It cannot be extended to other regions; 2) A multi-attribute decision-making method that considers social and economic factors, but there are still many problems to be solved in this method, such as the standardization of different indicators and the determination of indicator weights still need further research. More importantly, The calculation results cannot be compared with other regions; 3) Machine learning method, as a new method, has also received more and more attention, but the flood influencing factors basically present an obvious nonlinear relationship, so the data volume required for the training set is extremely demanding. large, and this is one of the unresolved difficulties

Many studies have shown that the factors affecting flood disasters are numerous, complex and interrelated, and may even present a non-linear situation, which is even more complicated if social and economic data are involved

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