Research On Coastal Storm Surge Disaster Of Bohai And Huanghai

Storm surge is a disaster of strong ocean dynamic processes. China is one of those countries which suffer from both tropical and temperate-cyclones storm surge. The destruction of storm surge is unbelievably enormous. We could only use words such like thousands, millions, even billions to describe how much we lost. Therefore, it means a lot to do storm surge prediction and evaluation well. Storm surge forecasts are generally divided into "experience statistical prediction" and "Dynamics-NWP" two categories. Disaster risk assessment is a new study combining risk studies with disaster studies, which focuses on the disaster and the loss of the uncertainty factors. At present, the risk assessment methods for storm surge include mathematical modeling, fuzzy mathematics, probability and statistics, the gray system theory, soft computing etc, and they all work well.In this paper, based on previous studies, using numerical prediction method, several issues in predictions of storm surge were studied, and using actual data the results of the study were also tested. Experiments show, that it did help on the current forecast of storm surge and related disaster prevention and reduction.Firstly, the simulation of the severe storm process was mainly studied. Due to the whole space when the storm surge occurs is a complex space-time simulation problem, it is important to choose a appropriate storm surge disaster prediction model. Accurately estimating and analyzing of the storm needs the numerical simulation of the tidal wave conditions. According to the simulation effect, Analysis of the scope and period of the flood caused by the storm, then determine the extent of damage and corresponding measures should be taken.The third chapter analysis the natural disaster risk assessment principles on the basis of content of risk. When samples is not enough, all samples give us to knowledge of the risk is not complete. Because of incomplete information is a kind of fuzzy information. According to the principle of information diffusion, there must be an appropriate diffusion function to compensate for the incomplete of samples and realize the high accuracy of risk assessment. This part adopts the related principles of the fuzzy information graining and information diffusion way to put forward to a risk evaluation model based on a small sample of fuzzy risk. By analyzing and evaluating the risk of China's coastal super-large typhoon storm, the forecasting results are consistent with the actual situation. In respect of prevention disaster and reducing loss the risk evaluation model has certain directive role.Then, from the historical data, we collected some indicator data, the day before the extreme high tide coming, including measured high tide, typhoon parameters, atmospheric pressure parameters and extreme high tide. Using three linear regression analyses, we build the relationship between these indicators and the corresponding extreme high tide, and estimate this relationship with various statistical tests. Since the data at different times have different effect on extreme high tides, we introduce a appropriate weight function. On this basis, the statistical prediction model about a extreme high tide is auto, and can be used for real-time forecasting because of low amount of calculation. The prediction model is effective during 24 hours, and in practice has good results, so the model is suitable for widespread use.Furthermore, one main kind of fuzzy information in geology calamity predicting system is solved by fuzzy information granulation method and information diffusion method separately. It is caused by the fuzzy information brought by incomplete data. The whole process is as follows:Firstly, influential information, for example typhoon and upstream surge, is collected by single step predicting model and neural network predicting model separately to predict the extreme tide level. Secondly, information diffusion method is applied to dig up information as much as possible to improve the precision of risk recognition under the condition that the information is not enough.Then, with the support of the data from numerical prediction, the paper developed a visualization system based on visualization software. The visualization system combined the data from the geographic information system and displayed both the terrain and tidal level on sea shore areas. This provides a visual and direct way to show the situation on sea shore areas when the storm surge attacks. Meanwhile, based on the risk evaluation model, the system can show the risk to meet disaster in a visual way, which provides a foundation of disaster prevention and reduction. The experiment, based on factual data, proved the system can display data quickly and accurately. It has ability to support the decision-making in the storm surge disaster.