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1.
The Joint-Probability Method (JPM) was adopted by federal agencies for critical post-Katrina determinations of hurricane surge frequencies. In standard JPM implementations, it is necessary to consider a very large number of combinations of storm parameters, and each such combination (or synthetic storm) requires the simulation of wind, waves, and surge. The tools used to model the wave and surge phenomena have improved greatly in recent years, but this improvement and the use of very large high-resolution grids have made the computations both time-consuming and expensive. In order to ease the computational burden, two independent approaches have been developed to reduce the number of storm surge simulations that are required. Both of these so-called JPM-OS (JPM-Optimal Sampling) methods seek to accurately cover the entire storm parameter space through optimum selection of a small number of parameter values so as to minimize the number of required storm simulations. Tests done for the Mississippi coast showed that the accuracy of the two methods is comparable to that of a full JPM analysis, with a reduction of an order of magnitude or more in the computational effort. 相似文献
2.
热带气旋资料长度对风暴潮危险性评估结果的影响 总被引：1，自引：1，他引：0
热带气旋历史样本数不足一直困扰着风暴潮风险评估研究,本文基于西北太平洋62 a(1949-2010年)历史观测热带气旋事件集资料和用随机模拟方法构造的1000 a模拟热带气旋随机事件集,以福建省连江县为例,开展了资料长度对风暴潮灾害危险性评估结果的影响分析。文中用ADCIRC模型模拟了两种数据集强迫下的风暴潮增水,采用极值Ⅰ型分布法得到了典型重现期的风暴潮增水,经过对计算结果分析发现典型重现期的风暴潮增水计算结果与所用数据资料长度有着密切相关性,数据资料越长,结果越稳定。对于1000 a一遇的风暴潮增水值,使用500 a长度的资料已经趋于稳定,并接近用1000 a资料计算得到的结果。在进行风暴潮危险性评估时,相比用几十年尺度的热带气旋历史数据集,1000 a的热带气旋模拟数据集的计算结果更具实际意义。 相似文献
3.
本文提出了一种基于Dempster-Shafer证据理论的风暴潮灾害损失评估方法。鉴于风暴潮致灾过程中的不确定性, 选择合适的具有代表性指标(包括最大风暴潮增水、最大有效波高和防灾减灾能力)产生灾害损失评估的证据, 并根据所选指标和风暴潮直接经济损失之间的相关性大小确定证据权重, 最后采用改进的Murphy证据融合算法进行证据融合, 从而判断灾害损失等级。通过实证分析发现, 本文所提出的方法在判断风暴潮灾害损失等级上的正确率达到93.1%, 优于朴素贝叶斯、支持向量机、神经网络和决策树等常用方法, 同时本文方法计算简便, 且随着训练集样本量的增加, 损失评估结果可进一步精细化。 相似文献
4.
It is known from data analysis that periodic fluctuations are obviously present in theprocess curve representing a storm surge in either the Huanghai Sea or the East China Sea,which has been obtained on the basis of the difference-estimating method. Apart from long-wave effects by storm disturbance, there is a nonlinear interaction between storm surge and 相似文献
5.
Harper, B.A. and Sobey, R.J., 1983. Open-boundary conditions for open-coast hurricane storm surge. Coastal Eng., 7: 41–60.The specification of realistic open-boundary conditions for the numerical simulation of hurricane (or tropical cyclone) storm surge is considered in the context of the very considerable spatial extent of the meteorological forcing. Existing practice is reviewed and an alternative approach, a Bathystrophic Storm Tide approximation to open-boundary water levels, is presented. Results from a series of numerical experiments demonstrate the advantages of this approach over existing methods. 相似文献
6.
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. 相似文献
7.
Kalman滤波风暴潮数值预报四维同化模式研究进展 总被引：1，自引：1，他引：1
本文首先介绍了Kalman滤波在风暴潮数值预报中的应用，特别介绍了近年来国际上发展的一些在实际中可行的次优化Kalman滤波算法。并通过一个稳态Kalman滤波风暴潮数值预报模式的实例表明，使用资料同化可以明显改进风暴潮后报结果；资料同化能够提供更为合理的预报初始场，对风暴潮的短期预报有较明显的改进。一旦没有资料同化到模式中去，预报结果很快接近确定性模式。 相似文献
8.
风暴潮是一种复杂的对众多因素敏感又备受关注的海洋现象。本文基于协方差局地化的集合卡尔曼滤波方法（EnKF）,选择201810号台风“安比”登陆上海的风暴潮过程,首次将海洋站和FVCOM数值模拟的不同来源、不同误差信息、不同时空分辨率的风暴潮进行数据同化融合,获得了逐72 h的上海海域风暴潮的最优解,进行了同化结果评估验证,并给出了集合样本数和Schur半径设置范围。结果表明,实测计算和数值模拟的风暴增减水之间均方根误差为0.20 m,实测和同化计算的风暴增减水之间均方根误差为0.07 m,准确度提高了65%;独立观测和同化计算的风暴增减水均方根误差为0.09 m,集合离散度与均方根误差比值为0.90,同化效果较好且可信;同化后的风暴增减水能够较好地刻画双峰增水、台风眼增水、增水锋面等特征,对于风暴潮研究、数值模拟结果订正、海洋防灾减灾等有重要意义。 相似文献
9.
确定风暴潮淹没范围是风暴潮灾害损失评估工作的核心内容。为提高海洋灾害调查水平,全面掌握灾害影响情况和制定灾害应对措施,文章梳理确定风暴潮淹没范围的主要方式,即遥感和现场调查;重点介绍现场调查手段的4种确定方法,即通过淹没痕迹、漂浮物聚集位置、植被变化和现场询问确定,并分别提出调查结果的可靠性判定方法;以2018年第8号台风"玛莉亚"造成的风暴潮淹没影响为实例,综合采用查找淹没痕迹、查找漂浮物聚集位置和现场询问3种方法,确定牙城镇风暴潮的淹没范围约为91.7万m2。研究结果表明:与采用遥感手段确定淹没范围相比,现场调查结果更具准确性和科学性,可适用于小规模淹没范围的确定,相关方法可行有效。 相似文献
10.
To avoid property loss and reduce risk caused by typhoon surges, accurate prediction of surge deviation is an important task. Many conventional numerical methods and experimental methods for typhoon surge forecasting have been investigated, but it is still a complex ocean engineering problem. In this paper, support vector regression (SVR), an emerging artificial intelligence tool in forecasting storm surges is applied. The original data of Longdong station at Taiwan ‘invaded directly by the Aere typhoon’ are considered to verify the present model. Comparisons with the numerical methods and neural network indicate that storm surges and surge deviations can be efficiently predicted using SVR. 相似文献
11.
A critical component of flood protection in some coastal areas is expected to be the potential contribution of wetlands to the lowering of surges as they propagate inland from the coast. Consequently, an accurate method to quantify the effect of wetlands on coastal surge levels is required. The degree to which wetlands attenuate surge is the subject of debate and difficult to assess. The potential of wetlands to reduce storm surge has typically been expressed as a constant attenuation rate, but the relationship is much more complex. A numerical storm surge model was applied to assess the sensitivity of surge response to specified wetland loss. Results suggest that wetlands do have the potential to reduce surges but the magnitude of attenuation is dependent on the surrounding coastal landscape and the strength and duration of the storm forcing. Numerical models that simulate the relevant physical processes can provide valuable information on how to best integrate wetlands into coastal protection plans. However, while the model applied for this study has displayed skill in estimating surges over wetlands, the formulations are missing key processes and model advancements are necessary. 相似文献
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13.
An approach to utilizing adaptive mesh refinement algorithms for storm surge modeling is proposed. Currently numerical models exist that can resolve the details of coastal regions but are often too costly to be run in an ensemble forecasting framework without significant computing resources. The application of adaptive mesh refinement algorithms substantially lowers the computational cost of a storm surge model run while retaining much of the desired coastal resolution. The approach presented is implemented in the GeoClaw framework and compared to ADCIRC for Hurricane Ike along with observed tide gauge data and the computational cost of each model run. 相似文献
14.
The effects of hurricane forward speed(V) and approach angle(θ) on storm surge are important and a systematic investigation covering possible and continuous ranges of these parameters has not been done before. Here we present such a study with a numerical experiment using the Finite Volume Community Ocean Model(FVCOM).The hurricane track is simplified as a straight line, such that V and θ fully define the motion of the hurricane. The maximum surge is contributed by both free waves and a forced storm surge wave moving with the hurricane.Among the free waves, Kelvin-type waves can only propagate in the down-coast direction. Simulations show that those waves can only have a significant positive storm surge when the hurricane velocity has a down-coast component. The optimal values of V and θ that maximize the storm surge in an idealized semi-circular ocean basin are functions of the bathymetry. For a constant bathymetry, the maximum surge occurs when the hurricane approaches the coast from the normal direction when the free wave generation is minimal; for a stepped bathymetry, the maximum surge occurs at a certain acute approach angle which maximizes the duration of persistent wind forcing; a step-like bathymetry with a sloped shelf is similar to the stepped bathymetry, with the added possibility of landfall resonance when the free and forced waves are moving at about the same velocity. For other cases, the storm surge is smaller, given other parameters(hurricane size, maximum wind speed, etc.)unchanged. 相似文献
15.
基于多种神经网络的风暴潮增水预测方法的比较分析 总被引：1，自引：0，他引：1
简要介绍了利用BP神经网络、小波神经网络、递归神经网络进行风暴潮增水值预测的原理。选取广东省珠江口以南的阳江站2017年风暴潮增水数据进行测试。结果表明,三种神经网络方法针对阳江地区风暴潮增水的预测均具有可靠性和实用性。以当前增水值为输入量的单因子模型更能反映真实风暴潮增水趋势,而从增水极值预测的准确性来看,以台风风力、气压、风向等相关参数为输入量的多因子模型优于单因子模型。BP神经网络更适用于多因子长时间预测,小波神经网络在单因子短时间预测上准确性更高,递归神经网络预测值与实测值相关性更强。在工程运用中,需根据地域时空特点、数据资料的丰富度与预测值评估指标选择合适的方法。 相似文献
16.
由于风暴潮灾害常年对我国造成严重影响,因此国内许多沿海省(自治区、直辖市)均开展了风暴潮灾害风险评估与区划工作。随着该工作的陆续完成,考虑全局风暴潮灾害风险管理的需要,即将面临相邻地区成果衔接或集成的问题。为此,文章开展了相邻地区风暴潮灾害风险评估与区划成果集成方法的初步研究,提出潮位、增水、淹没水深、危险性、脆弱性、风险等级和风险区划等模型计算或评估结果的分类集成方法,并以上海市沿海5区的3个区域风暴潮模型的计算和评估结果为基础进行了方法应用,成功获得了上海全市的集成成果。文章提出的成果集成方法旨在为全国其他沿海省(自治区、直辖市)、县的成果集成提供方法借鉴。 相似文献
17.
System Analysis of Disaster Prevention Design Criteria for Coastal and Estuarine Cities 总被引：3，自引：0，他引：3
—In China,estuarine and coastal cities are mostly regional economic development centers.Thedisasters by combined effect of upper reach flood,storm surge and typhoon waves are primary obstaclesto the economic development of such cities.Thus the risk analysis and system analysis of flood-stormsurge-wave disaster,economic loss and flood-storm surge control measures play a very important role inthe sustainable development of coastal cities.There are three types of coastal cities for consideration.Thefirst type of city is like Tianjin.The most significant damage is from the upper reach flood.The effect ofstorm surge is negligible,because in the estuary of the Haihe River,tidal locks are built.The Grey MarkovModel(GMM)is used to forecast the flood peak level.GMM combines the Grey system and the Markovtheory into a high-precision model.The predicted flood peak levels are close to the measured data.A syn-thetic model is established for economic assessment,risk analysis and flood-control benefit estimation.Asa n 相似文献
18.
《Coastal Engineering》2004,51(4):277-296
A cyclone induced storm surge and flood forecasting system that has been developed for the northern Bay of Bengal is presented. The developed system includes a cyclone forecasting model that uses statistical models for forecasting of the cyclone track and maximum wind speed, and an analytical cyclone model for generation of cyclone wind and pressure fields. A data assimilation system has been developed that allows updating of the cyclone parameters based on air pressure and wind speed observations from surface meteorological stations. The forecasted air pressure and wind fields are used as input in a 2D hydrodynamic model for forecasting storm surge levels and associated flooding. An efficient uncertainty prediction procedure based on Harr's point estimation method has been implemented as part of the forecasting system for prediction of the uncertainties of the forecasted storm surge levels and inundation areas caused by the uncertainties in the cyclone track and wind speed forecasts. The developed system is applied on a severe cyclone that hit Bangladesh in April 1991. The simulated storm surge and associated flooding are highly sensitive to the cyclone data. The cyclone data assimilation system provides a more accurate cyclone track when the cyclone approaches the coastline, which results in a significant improvement of the storm surge and flood predictions. Application of the uncertainty prediction procedure shows that the large uncertainties of the cyclone track and intensity forecasts result in large uncertainties of the forecasted storm surge levels and flood extend. The forecasting system shows very good forecasting capabilities up to 24 h before the actual landfall. 相似文献
19.
本文建立一个温带风暴潮模式，包括海上边界层风场模式和风暴潮数值模式。利用建立的温带风暴潮模式，模拟了影响连云港的几次显著温带风暴潮过程，结果表明，本模式所采用的海上边界层风场模式和风暴潮数值模式是匹配的，能够满足海洋工程中的风暴潮数值计算的需要，甚至可以成为日常温带风暴潮数值预报的有用手段。 相似文献
20.
为了研究随机事件集实际应用于计算南通如东岸段风暴增水的合理性问题,基于ADCIRC模型模拟影响南通如东岸段基于随机事件集的风暴增水,然后利用P-Ⅲ型曲线对年增水极值进行拟合,得到各典型重现期下的增水值,并与由28年历史资料拟合得到的各重现期下增水值进行对比。结果表明,在历史资料长度所及的28年以及以下重现期,基于随机事件集模拟得到的重现期增水值与基于历史实测资料的比较符合,说明随机事件集的结果在低重现期情况下结果良好。对于高重现期增水值,基于随机事件集的拟合结果显著大于基于历史资料的拟合结果。由于历史资料时间太短,不足以发生非常极端的风暴潮事件,故对高重现期的拟合结果难以保证可信度,所以不能排除随机事件集拟合结果的合理性。随机事件集在南通如东岸段对低重现期增水估计准确,同时也能较充分地估计高重现期增水,在目前缺乏百年千年时间尺度的实测资料的情况下,不失为一种良好的风暴增水重现期计算工具。在全球变暖情况下,超强台风出现几率大大增加,典型重现期增水值也会相应提高,为了预防风暴灾害的侵袭,需要加深加固海堤、江堤等海岸工程。 相似文献