Abstract. China is one of the countries that is most seriously affected by storm surges. In recent years, storm surges in coastal areas of China have caused huge economic losses and a large number of human casualties. Knowledge of the inundation range and water depth of storm surges under different typhoon intensities could assist predisaster risk assessment and making evacuation plans, as well as provide decision support for responding to storm surges. Taking Pingyang County in Zhejiang Province as a case study area, parameters including typhoon tracks, radius of maximum wind speed, astronomical tide, and upstream flood runoff were determined for different typhoon intensities. Numerical simulations were conducted using these parameters to investigate the inundation range and water depth distribution of storm surges in Pingyang County considering the impact of seawall collapse under five different intensity scenarios (corresponding to minimum central pressure values equal to 915, 925, 935, 945, and 965 hPa). The inundated area ranged from 103.51 to 233.16 km2 for the most intense typhoon. The proposed method could be easily adopted in various coastal counties and serves as an effective tool for decision-making in storm surge disaster risk reduction practices.

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In the design of offshore platforms, the height of the bottom deck directly affects the safety and engineering cost of the entire platform. It is a very important scale parameter in platform planning. The American Petroleum Institute (API) specification shows that the key to determining the height of the bottom deck lies in the wave height and calculation of the return level of the water increase. Based on the perspective of stochastic processes, this paper constructs a new distribution function model for joint parameter estimation of the marine environment. The new model uses a family of random variables to show the statistical characteristics of design wave height and water increase in both time and space, with extreme value expanded EED-I type distribution used as marginal distribution. The new model performs statistical analysis on the measured hydrological data of the Naozhou Station during the flood period from 1990 to 2016. The Gumbel–Copula structure function is used as the connection function, and the compound distribution model of the wave height and the water increase is used to obtain the joint return level of the wave height and the water increase and through which the bottom deck height of the area is calculated. The results show that the stochastic compound distribution improves the issue of the high design value caused by simple superposition of univariate return levels. The EED-I type distribution still has good stability under the condition of less measured data. Thus, under the premise of ensuring the safety of the offshore platform, less measured data can still be used to calculate the height of the bottom deck more accurately.

In the context of climate change where natural disasters are frequent, assessing disaster risk can provide great help for relevant risk decisions. Based on the loss expectation theory, this paper proposes a method for quantitatively assessing typhoon disaster risk. In particular, the probability of typhoon occurrence is calculated by fitting the best structure function of the samples to the joint distribution of wave height, water increase, and wind speed. The loss expectation is then expressed as the product of the typhoon occurrence probability and the aversion utility loss, which is used to quantify the loss result of a typhoon disaster. In addition, a risk level map is created using the theory of aversion utility, with the direct economic loss rate and the proportion of disaster-affected population as indicators. The calculation results show that the absolute loss value considering the aversion utility is slightly higher than the product of the probability and the loss value, indicating that the new model reflects the social group's aversion to typhoon disaster risk. The diagram of risk level zoning showed that, excluding typhoon No.1306 Rumbia, the risk level assessments of the remaining typhoons, in accordance with affected population and direct economic loss, were basically consistent. This evaluation model, the outcomes of which can serve as a foundation and reference for certain risk assessment and decision-making, has some feasibility and practicability.