Modeling of coupled tide–wave–surge process in the Yellow Sea

A coupled wave–tide–surge model has been developed in this study in order to investigate the effect of the interactions among tides, storm surges, and wind waves. The coupled model is based on the synchronous dynamic coupling of a third-generation wave model, WAM cycle 4, and the two-dimensional tide–surge model. The surface stress, which is generated by interactions between wind and wave, is calculated by using the WAM model directly based on an analytical approximation of the results using the quasi-linear theory of wave generation. The changes in bottom friction are created by the interactions between waves and currents and calculated by using simplified bottom boundary layer model. In consequence, the combined wave–current-induced bottom velocity and effective bottom drag coefficient were increased in the shallow waters during the strong storm conditions.     

A synchronously coupled tide–wave–surge model of the Yellow Sea

A coupled wave–tide–surge model has been established in this study in order to investigate the effect of tides, storm surges, and wind waves interactions during a winter monsoon on November 1983 in the Yellow Sea. The coupled model is based on the synchronous dynamic coupling of a third-generation wave model, WAM-Cycle 4, and the two-dimensional tide–surge model. The surface stress generated by interactions between wind and waves is calculated using the WAM-Cycle 4 directly based on an analytical approximation of the results obtained from the quasi-linear theory of wave generation. The changes of bottom friction factor generated by waves and current interactions are calculated by using simplified bottom boundary layer model. The model simulations showed that bottom velocity and effective bottom drag coefficient induced by combination of wave and current were increased in shallow waters of up to 50 m in the Yellow Sea during the wintertime strong storm conditions.     

Frequency of tidal storm surge at New York harbor (New York) and Newark bay (New Jersey)

A joint probability analysis of storm tides is made for the Battery, New York (U.S.A.), and Newark Bay, New Jersey (U.S.A.). Storm tides are caused by either low-pressure coastal storms (northeasters) or hurricanes. The analysis uses existing gage data at the Battery to construct frequency/probability curves of peak surge elevations and tidal amplitudes. These are used in a computer program to combine standard storm surge stages and tidal stage curves to produce an artificial storm tide with given peak elevation and incremental frequency. These peak elevations and incremental frequencies are ranked to produce cumulative frequency curves for northeasters and hurricanes. A frequency curve is obtained for Newark Bay via correlation.     

A numerical study on the impact of tidal waves on the storm surge in the north of Liaodong Bay

A storm surge is an abnormal sharp rise or fall in the seawater level produced by the strong wind and low pressure field of an approaching storm system.A storm tide is a water level rise or fall caused by the combined effect of the storm surge and an astronomical tide.The storm surge depends on many factors,such as the tracks of typhoon movement,the intensity of typhoon,the topography of sea area,the amplitude of tidal wave,the period during which the storm surge couples with the tidal wave.When coupling with different parts of a tidal wave,the storm surges caused by a typhoon vary widely.The variation of the storm surges is studied.An once-in-a-century storm surge was caused by Typhoon 7203 at Huludao Port in the north of the Liaodong Bay from July 26th to 27th,1972.The maximum storm surge is about 1.90 m.The wind field and pressure field used in numerical simulations in the research were derived from the historical data of the Typhoon 7203 from July 23rd to 28th,1972.DHI Mike21 is used as the software tools.The whole Bohai Sea is defined as the computational domain.The numerical simulation models are forced with sea levels at water boundaries,that is the tide along the Bohai Straits from July 18th to 29th（2012）.The tide wave and the storm tides caused by the wind field and pressure field mentioned above are calculated in the numerical simulations.The coupling processes of storm surges and tidal waves are simulated in the following way.The first simulation start date and time are 00：00 July 18th,2012; the second simulation start date and time are 03：00 July 18th,2012.There is a three-hour lag between the start date and time of the simulation and that of the former one,the last simulation start date and time are 00：00 July 25th,2012.All the simulations have a same duration of 5 days,which is same as the time length of typhoon data.With the first day and the second day simulation output,which is affected by the initial field,being ignored,only the 3rd to 5th day simulation results are used to study the rules of the storm surges in the north of the Liaodong Bay.In total,57 cases are calculated and analyzed,including the coupling effects between the storm surge and a tidal wave during different tidal durations and on different tidal levels.Based on the results of the 57 numerical examples,the following conclusions are obtained：For the same location,the maximum storm surges are determined by the primary vibration（the storm tide keeps rising quickly） duration and tidal duration.If the primary vibration duration is a part of the flood tidal duration,the maximum storm surge is lower（1.01,1.05 and 1.37 m at the Huludao Port,the Daling Estuary and the Liaohe Estuary respectively）.If the primary vibration duration is a part of the ebb tidal duration,the maximum storm surge is higher（1.92,2.05 and 2.80 m at the Huludao Port,the Daling Estuary and the Liaohe Estuary respectively）.In the mean time,the sea level restrains the growth of storm surges.The hour of the highest storm tide has a margin of error of plus or minus 80 min,comparing the high water hour of the astronomical tide,in the north of the Liaodong Bay.     

黄河河口三角洲风暴潮灾害特点及其预防对策

黄河河口三角洲地区是风暴潮灾害的多发地区,研究该地区风暴潮的成因及其特点,是有效预防风暴潮灾害的基础。在对风暴潮成因分析的基础上,重点研究了各类风暴潮的特点,并提出预防风暴潮灾害的对策措施。     

渤、黄海天文潮—风暴潮相互作用及其对极值水位的贡献

基于Delft3D模型建立了中国渤、黄海风暴潮数值模型,选取1979—2020年影响该海域的93场风暴过程（包括台风、寒潮和温带气旋）,模拟了所产生的风暴增水和风暴潮总水位。采用泊松—皮尔逊复合极值分布理论,推算了渤、黄海对应不同重现期的极值水位;通过数值试验,对天文潮—风暴潮非线性相互作用对极值水位的贡献进行了量化分析。研究结果表明,渤海的莱州湾、渤海湾,以及黄海的江华湾、西朝鲜湾风暴增水最大,其中江华湾北侧和渤海湾西南侧的百年一遇风暴增水可达4 m;天文潮—风暴潮非线性相互作用在潮差较大、水深较浅的河口、湾顶区域更为显著,与耦合模型结果相比,非线性作用使极值水位值偏小,天文潮、风暴潮增水的线性叠加可显著高估极值水位,高估的幅值可达0.5~0.8 m。考虑重现期极值水位是海岸灾害防护工程的关键设计参数之一,对海岸构筑物的安全和建造成本影响极大,应重视天文潮—风暴潮非线性相互作用对重现期水位的影响。     

The hydrodynamic response of the York River estuary to Tropical Cyclone Isabel, 2003

Hurricane Isabel made landfall along the North Carolina coast on September 18, 2003 (UTC 17:00) and the storm surge exceeded 2.0 m in many areas of the Chesapeake Bay and in the York River estuary. River flooding occurred subsequently, and the peak river discharge reached 317 and 104 m³ s⁻¹ in the Pamunkey and Mattaponi rivers, respectively. The York River estuary experienced both storm surge and river flooding during the event and the estuary dynamics changed dramatically. This study investigates the hydrodynamics of the York River estuary in response to the storm surge and high river inflows. A three-dimensional model was used to investigate the changes of estuarine stratification, longitudinal circulation, salt flux mechanisms, and the recovery time required for the estuary to return to its naturally evolved condition without the storm. Results show that the salt flux was mainly caused by advection, which was induced by the barotropic gradient during the storm event. The net salt flux increased by a factor of 30 during the rise of the storm surge. However, the large amount of salt transported into the estuary was quickly transported out of the estuary as the barotropic gradient reversed during the descent of the storm surge. Subsequent high freshwater inflow influenced the estuarine circulation substantially. The estuary changed from a partially mixed estuary to a very stratified estuary for a prolonged period. The model results show that it will take about 4 months for the estuary to recover to its naturally evolved salinity distribution after the impacts of the storm surge and freshwater pulse.     

不同路径台风作用下长江下游沿线风暴增水分布研究

长江口受台风影响严重,台风风暴潮、上游洪峰及天文大潮相遇将致使长江下游至长江口水位暴涨,对沿岸至河口的防汛安全构成严重威胁。基于ADCIRC模型构建东中国海至长江口风暴潮数学模型,模拟9711号台风和0012号台风两场典型台风水位过程。以典型台风为基础构成多种台风路径,分析不同登陆位置和走向对长江沿线风暴增水影响。研究大洪水、不同路径台风、天文大潮共同影响下长江下游沿线风暴增水分布规律。结果表明:登陆位置处于长江口南侧情况下长江河道沿线增水大于正面登陆长江口和北侧登陆型台风;平行于长江河道方向移动的台风造成沿线增水大于斜向穿越长江口的台风,不同台风走向对于风暴增水影响程度小于登陆位置;台风风暴潮、上游洪峰及天文大潮“三碰头”情形下长江沿线增水分布呈单峰型,从大通至江阴不断增大,江阴至中浚维持高位,中浚至口外迅速减小。     

海岸工程对渤海湾风暴潮高潮位影响分析

渤海湾是全世界受风暴潮灾害最严重的地区之一。近年来渤海湾建设了大量的大型海岸工程,为研究其建设以后风暴潮可能发生的变化,采用大-中-小区域多重嵌套方法,建立渤海风暴潮二维数值模型。以对渤海海域影响最显著的9216、9711台风和2003年10月三次风暴潮为例,对渤海湾大型工程实施前、后的风暴潮过程进行模拟,分析工程实施后风暴潮高潮水位变化,为工程实施可能对风暴潮防护带来的影响提供基础。计算表明,由于沿岸围垦减小海域的纳潮受水面积,海水被挤压抬升,渤海湾海域工程后风暴潮高潮位普遍抬升。在特大风暴潮作用下,水位最大升高可达0.10 m以上,在堤防设计中需引起重视。     

基于海气耦合模型的渤海两种类型风暴潮数值模拟与对比分析

渤海一年四季都易受到由温带风暴和热带气旋所致风暴潮的影响。为了缓解风暴潮灾害对海岸地区人员生命财产的影响，十分有必要了解大型风暴潮的发生过程和机制。目前大部分研究主要局限于单一的温带风暴潮或台风风暴潮。本文利用所构建的海气耦合数值模型研究了发生于渤海的两种类型的风暴潮，对发生在渤海的2次典型强风暴潮过程进行了模拟。由WRF模型模拟得到的风场强度和最低海平面气压与实测数据吻合较好，由ROMS模型模拟得到的风暴潮期间水位变化过程与潮位站观测结果也吻合较好。对两种类型风暴潮期间的风场结钩、海面风应力、海洋表面平均流场以及水位分布进行了分析对比，并将耦合模型结果与非耦合模型结果进行了对比。研究表明，渤海两种类型风暴潮期间的风场结钩、海面风应力、海洋表面平均流场以及水位分布等均存在巨大差异。渤海风暴潮的强度主要由海洋表面的驱动力所决定，但同时也受海岸地形地貌的影响。     

Response of sediment dynamics in the York River Estuary,USA to tropical cyclone Isabel of 2003

Tropical Cyclone Isabel of 2003 generated large storm surge, strong waves, and subsequent river flooding in the York River Estuary, USA during its passage across the Chesapeake Bay region. A 3D model was used to investigate the changes of sediment concentration, sediment flux, and the recovery time of the York River Estuary to its naturally evolved condition without the storm. The results showed that two sediment concentration peaks appeared during the storm event. The first one was induced by the large upstream flow and waves during the storm surge rising period, and the later one was caused by the strong downstream flow during the descent of the storm surge. The advection, which was induced by the barotropic gradient, dominated the sediment flux during the storm event. The sediment fluxes increased by a factor of 100 during the rise and descent of the storm surge. A large amount of sediment that was transported into the estuary and eroded from the seabed during the rising of the storm surge was quickly transported out of the estuary during the descent of the storm surge. Waves played a key role in stirring the seabed and increasing the sediment concentration during the storm. Subsequent high freshwater inflow changed the sediment loading and hydrodynamics in the estuary, and thus, influenced the estuarine turbidity maximum (ETM) dynamics profoundly. The ETM moved downstream with the river flooding initially and returned upstream with the waning of river flooding and the re-establishment of gravitational circulation. The effect of river flooding on sediment concentration varied spatially and depended on the changes of ETM locations and vertical mixing. The model results suggest that a large amount of sediment was transported out of the estuary during the storm event and the subsequent river flooding had a larger impact on recovery time of the estuary.     

风暴潮三维数值计算模式的研究及在渤海湾的应用

以实验室二维温带风暴潮数值模型为基础,综合考虑海洋潮波动力与风应力联合作用,建立温带风暴潮三维数值计算模型.模型从推导三维风暴潮基本控制方程出发,并应用交替方向隐格式(ADI)方法对方程进行离散求解.对于浅水动边界,模型采取局部深槽、缩小水域的活动边界处理方法.利用拟三维数值计算方法,并提出了非平面水深等分模式和平面等水深分布模式,应用这两种计算模式分别对渤海湾2009年5月8～10日发生的风暴潮过程进行了数值模拟.将风暴潮位计算结果和增水位计算结果与塘沽验潮站的实际观测数值进行对比验证,结果显示受风应力与潮波联合作用的风暴潮位和增水位与实测数据吻合良好;通过比较得到了平面等水深分布模式的计算成果要比非平面水深等分模式的计算成果更接近观测资料的结论,为风暴潮预报提供了理论依据.     

山东沿岸历史风暴潮探讨

作者根据地方史志资料进行分析与统计,提出山东沿岸风暴潮的特点:存在风潮和台风暴潮两种型式。在风潮中,春季风潮占绝对优势,秋季风潮是次要的。三者的关系是:台风暴潮:春季风潮:秋季风潮=50％:37％:13％。此外,还分析了在风暴潮记载中的有关气象记录问题以及历代王朝有关风暴潮记录的特点。提出历史风暴潮灾情的个例,举出1985年山东沿岸发生的风暴潮灾情,以说明风暴潮灾害的严重性。     

Wave set-up in the storm surge along open coasts during Typhoon Anita

Wave set-up in storm surges is studied using a numerical model for coasts in Tosa Bay, Japan, open to the Pacific Ocean. Simulation models employing only atmospheric pressures and winds as external forces are unable to properly simulate open coast storm surge heights, such as those due to Typhoon Anita (1970). However, the present study shows that a numerical model incorporating wave-induced radiation stresses, as well as wind stresses and pressure gradients, is able to account for the open coast surge heights. There is a maximum contribution of 40% by the radiation stresses to the peak sea level rises. This study also evaluates the effects of the tides; including the tides improves the agreement between the predicted water surface elevations and the observations. The difference in predictions between one-way coupling from wave to surge models and two-way coupling of the surge and wave models is found to be small.     

海口港风暴潮分析与预报

本文根据海口港１９７１～１９８９年的实测潮位资料和有关文献,利用差值法分离出台风增减水的过程曲线,对海口港风暴潮的特性和引起增减水的物理机制进行了初步分析。采用经验方法确定了导致本站增水的主导风向及最大的区域,建立了增水极值与本站风力、气压的相互关系,并通过逐步回归分析,给出了海口港风暴潮过程预报方程。最后利用１９９０、１９９１两年的实测资料对预报方程进行了后报检验,结果表明,预报与实测值的吻合程度较好。     

Simulation of Storm Surges in the Bay of Bengal Using One-Way Coupling Between NMM-WRF and IITD Storm Surge Model

The storm surge associated with severe tropical cyclones (TCs) in the Bay of Bengal (BoB) is a serious concern along the coastal regions of India, Bangladesh, Myanmar, and Sri Lanka. It is one of the most hazardous elements associated with landfalling TCs other than strong winds and heavy precipitation and about 75% of the casualities in this region are attributed to storm surges. Therefore, it is highly essential to predict the storm surges with greater accuracy at least 2 days in advance for effective evacuation. In the present study, an attempt is made to simulate the storm surges associated with severe TCs in the BoB using one-way coupling of the Non-hydrostatic Mesoscale Model core of Weather Research and Forecasting (NMM-WRF) system with the two-dimensional finite-difference storm surge model developed at the Indian Institute of Technology Delhi (IITD). The NMM-WRF model simulated track, pressure drop, and radius of maximum wind are used to calculate the wind-stress through Jelesnianski wind formulation. The results are compared with the observed/estimated values as provided by the operational/meteorological agencies of India, Bangladesh, and Myanmar. This study suggests that using simulated surface meteorological fields of a high-resolution mesoscale model, the storm surge can be predicted at least 2 days in advance of the actual landfall of TCs with reasonable accuracy. This approach will be helpful in providing disastrous storm warning well in advance in a coastal region, which will help with rapid evacuation from the vulnerable coastal region, relocation as well as protection of valuables, disaster mitigation, and coastal zone management.     

Landward limit of wind setup on beaches

Open coast storm surge water levels consist of a wind shear forcing component generally referred to as wind setup; a wave setup component caused by wind-induced waves transferring momentum to the water column; an atmospheric pressure head component due to the atmospheric pressure deficit over the spatial extent of the storm system; a Coriolis-forced component due to effects of the rotation of the earth acting on the wind-driven alongshore current at the coast; and, if astronomical tides are present, an astronomical tide component. Astronomical tide is considered to be predictable and, therefore, not a meteorological driven component of storm surge although there may be interaction between the tide and meteorological driven water levels. Typically the most important component of storm surge on the US East Coast and Gulf of Mexico shorelines is the wind setup component. The importance of inland flooding due to the wind setup component of storm surge is considered herein with special reference to the effect of subaerial slope on inland flooding where three different linear slopes are considered and storm surge is calculated for the region above still water level, using an analytic solution. The present study findings show that the inland storm surge from the wind setup component can be of considerable importance and lead to significantly higher storm surges than found for storm surge at the still water level intersection of the beach/land. It is shown that mild slopes can lead to very high water levels at the land–water interface (i.e. above the still water level intersection of the beach).     

山东省水文系统防潮减灾经验及建议

本文简要介绍了山东省历史上发生的风暴潮灾害情况，总结了山东省水文系统50多年来在防潮减灾工作中取得的四条经验。在勘测搜集的潮汐水文资料基础上，研制了莱州湾代表站的风暴潮预报方案，积极开展了风暴潮监测预报，直接服务于各级政府的防潮减灾，取得了巨大的经济效益和社会效益。     

河北省沿海风暴潮特征及成因分析

以秦皇岛、京唐港、曹妃甸、黄骅4个验潮站的实测潮位和逐时风的数据为基础,以2013年河北省政府发布的风暴潮四色警戒潮位值为标准,统计了2008-2017年10 a河北省沿海的风暴潮过程,从警报级别、区域分布、时间分布、天气系统、经济损失5个方面分析河北省沿海风暴潮特征,并从地形、天文潮与天气系统配合、海平面上升、全球变暖引发的气候异常4个方面分析了影响河北省沿海风暴潮的成因,分析得出:受天气系统的影响,7-10月是河北省风暴潮高发时段,且由于河北省岸线分布特点,沧州市沿海受到风暴潮影响的次数最多,唐山和秦皇岛次之,沧州和唐山地区的风暴潮过程多由东北向大风引起,而秦皇岛地区的风暴潮过程多由东南向风引起。     

Multi-step ahead short-term predictions of storm surge level using CNN and LSTM network

Storm surges pose significant danger and havoc to the coastal residents' safety, property, and lives, particularly at offshore locations with shallow water levels. Predictions of storm surges with hours of warning time are important for evacuation measures in low-lying regions and coastal management plans. In addition to experienced predictions and numerical models, artificial intelligence (AI) techniques are also being used widely for short-term storm surge prediction owing to their merits in good level of prediction accuracy and rapid computations. Convolutional neural network (CNN) and long short-term memory (LSTM) are two of the most important models among AI techniques. However, they have been scarcely utilised for surge level (SL) forecasting, and combinations of the two models are even rarer. This study applied CNN and LSTM both individually and in combination towards multi-step ahead short-term storm surge level prediction using observed SL and wind information. The architectures of the CNN, LSTM, and two sequential techniques of combining the models (LSTM–CNN and CNN–LSTM) were constructed via a trial-and-error approach and knowledge obtained from previous studies. As a case study, 11 a of hourly observed SL and wind data of the Xiuying Station, Hainan Province, China, were organised as inputs for training to verify the feasibility and superiority of the proposed models. The results show that CNN and LSTM had evident advantages over support vector regression (SVR) and multilayer perceptron (MLP), and the combined models outperformed the individual models (CNN and LSTM), mostly by 4％–6％. However, on comparing the model computed predictions during two severe typhoons that resulted in extreme storm surges, the accuracy was found to improve by over 10％ at all forecasting steps.