Application Of Typhoon Storm Surge-Wave Forecasting Model For Yangtze River Estuary

In recent years,the frequency of marine disasters has increased significantly,resulting in massive losses to coastal areas.Among these disasters,typhoons and storm surges stand out as the most significant,accounting for 38.1% of the total direct economic losses from marine disasters.As a result,coastal cities that are frequently affected by these calamities are in urgent need of a typhoon storm surge forecasting system that possesses the qualities of accuracy,speed,and convenience.Furthermore,it is worth noting that the propagation of typhoon waves nearshore is subject to nonlinear interactions with complex submarine topography and irregular shorelines.Consequently,the task of typhoon wave forecasting is more challenging than that of tide levels.Thus,the research and application of numerical prediction techniques for typhoon storm surges and waves are of paramount importance for disaster prevention and mitigation.The present study reports on the development of a hydrodynamic model that incorporates the effects of runoff,tides,typhoons,and waves.In conjunction with the collection of measured tide levels and water gain data from multiple significant stations in the Yangtze River estuary and Hangzhou Bay area,this model has enabled the updating of the shoreline and topography of the Yangtze River estuary region.Furthermore,the implementation of standardization measures for data flow format(NetCDF)and database storage of model calculation results have been achieved.To cater to the specific requirements of business users,the system operation interface was upgraded,allowing for the automatic acquisition or manual modification of the typhoon forecast path.Additionally,a GIS rendering function was incorporated,allowing for the combination of the calculated information,such as water level and water gain field,with the GIS layer for swift queries.Multiple hindcast and forecast validations were performed for the storm tide forecasting system,focusing on parameters of significant concern to the business,including the average relative error of storm tide level,the maximum forecast error of water gain within 24 hours,the time difference between high and low tide of storm tide level,and the error of the highest and lowest tide level.All verified typhoon cases demonstrated the model’s impressive accuracy,with the average relative error of storm tide level found to be less than 10%,and the maximum forecast error of water gain within 24 hours was less than 20 cm.Additionally,the phase error of average high tide level and maximum tide level was controlled within 25 minutes,while the error of high and low tide level was found to be less than 25 cm.Finally,the effectiveness of the developed model was verified through its deployment at the Taihu Basin Authority of Ministry of Water Resources and the Shanghai General Hydrographic Station,where it was successfully applied in the actual operation during the typhoons of 2021-2022.These findings highlight the immense potential of the developed model in supporting disaster prevention and mitigation efforts in coastal areas.To address the complex nature of wave forecasting during typhoons,a novel ensemble probabilistic forecasting approach is proposed in this study.Unlike conventional ensemble forecasting methods,this technique integrates both real-time forecast information and historical path data of typhoons,and generates an ensemble of typhoon forecast paths through similar path and probability analysis methods to form an ensemble forecast wind field.Furthermore,taking the water level and current field simulated by FVCOM as input,the significant wave height of nearshore waves in the study area during the typhoon is simulated by applying the wave numerical model(SWAN).To validate the effectiveness of the proposed method,hindcast validation and numerical experiments are conducted.The probability distribution of the significant wave height results is provided,and the probabilistic forecast results’ coverage compared to the measured results can reach up to 94% during the ensemble prediction period.Therefore,this approach is applicable for probabilistic prediction of near-shore wave elements under the influence of typhoons and provides novel techniques and ideas for probabilistic wave forecasting in near-shore waters.