Abstract
Storm surge has become an important factor restricting the economic and social development of China’s coastal regions. In order to improve the scientific judgment of future storm surge damage, a method of model groups is proposed to refine the evaluation of the loss due to storm surges. Due to the relative dispersion and poor regularity of the natural property data (login center air pressure, maximum wind speed, maximum storm water, super warning water level, etc.), storm surge disaster is divided based on eight kinds of storm surge disaster grade division methods combined with storm surge water, hypervigilance tide level, and disaster loss. The storm surge disaster loss measurement model groups consist of eight equations, and six major modules are constructed: storm surge disaster in agricultural loss, fishery loss, human resource loss, engineering facility loss, living facility loss, and direct economic loss. Finally, the support vector machine (SVM) model is used to evaluate the loss and the intra-sample prediction. It is indicated that the equations of the model groups can reflect in detail the relationship between the damage of storm surges and other related variables. Based on a comparison of the original value and the predicted value error, the model groups pass the test, providing scientific support and a decision basis for the early layout of disaster prevention and mitigation.
Highlights
Storm surges are abnormal coastal sea-level events caused by meteorological conditions, such as tropical cyclones
Domestic and foreign scholars have made a substantial amount of research on the prediction method: regression analysis, exponential smoothing, Bayesian Value at Risk (BVAR) model, and so on have been applied by some scholars to carry out forecast analysis; some scholars choose to use the combination forecasting method
The index data of the natural properties of storm surges is comprehensively integrated into the index of storm surge disaster intensity in order to prepare for the selection of model group equation variables
Summary
Storm surges are abnormal coastal sea-level events caused by meteorological conditions, such as tropical cyclones. In 1992, the Sea, Lake and Overland Surges from Hurricanes (SLOSH) model was used for the first time to estimate storm surge disaster loss in the United States. Based on the static input–output model, the concept of a time series was employed, and a dynamic input–output model was constructed to evaluate the indirect economic loss caused by natural disasters [23]. The proposed grey relational model based on dispersion of panel data has been used to research storm-tide disaster loss in China’s coastal [35]. A method of model groups is proposed for the first time to study storm surge damage.
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