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《中国海洋大学学报(自然科学版)》2017,(11)
基于沿海长期观测的历时潮位资料,提出了推求设计高(低)水位的传统最大熵分布模型。该分布能够拟合逐时潮位具有双峰的概率密度曲线,计算所得设计高(低)水位,与修改的最大熵分布高潮10%和低潮90%的水位值相比,误差较小。选型的历时潮位曲线分布为港口工程设计水位推算提供了更多的选择,计算精度高,克服了手工方法推算历时潮位设计值的不足,有理论和工程意义。 相似文献
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一、问题的提出 在近岸和港湾工程的波浪计算中,海浪工作者往往注重有关波浪要素的计算方法,而忽视计算重现期波高所需的水位值的选取问题。众所周知,波浪从较深水域传向近岸浅水区,尤其是港湾的传播过程中,由于水深变小和底摩擦的作用,波浪的能量发生了变化,对于各种重现波高而言,由于波高较大,因而,浅水因素的影响更为显著,特别是位于波浪破碎区内的海上结构物,其设计波高的大小完全由计算者所选取的水深值(结构物位置固定后,决定因素是水位值)所决定,因而,这个水位值的选取,是一个关系到结构物的安全和造价的重要问题。 相似文献
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在考虑了地形变化,水域开挖,建筑物的掩护,码头和防波堤的反射等对波浪影响的基础上,建立了青岛浮山湾海区波浪模型.计算网格采用矩形网格,为了减少误差,保证计算的精度,计算中均采用正向入射,岸滩按全吸收边界考虑.由模型计算得出各计算点在不同水位和浪向时50年一遇的比波高和波高值.为奥运赛场的建设规划提供了基础依据. 相似文献
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研究了天气频段非周期性水位振动与风和大气压力的关系，根据对水位振动，风和大气压力进行的谱分析，确定了大约在５，１０，１５￣２０ｄ周期存在天气最大值，为鹗霍次克海５个站建立了普通回归方程和谱回归方程，并对水位升高的观测值和计算值做了比较，可看出，使用谱回归方程的计算结果与线性回归方程计算结果相比较有实质性改善。 相似文献
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水位在忽略观测误差的前提下,可分解为潮位和余水位,后者具有较强的空间相关性以及非平稳特征,是影响水位预报精度的主要因素。港口工程、航运计划编制等方面对实时高精度水位预报具有重要需求,这对余水位预报模型构建提出了更高要求。另外,利用高精度余水位预报模型可减少验潮站布设数量。针对余水位短期预测模型精度不高的现状,本文对余水位进行集合经验模态(EEMD)分解,获得余水位在时间序列上的本征模函数(IMF);使用快速傅立叶变换(FFT)分析各本征模函数的频谱特征;再利用BP神经网络对各个本征模函数进行训练,预测了未来6 h、12 h、24 h的余水位值。对哥伦比亚河下游河口处的3组典型验潮站的余水位数据的预测结果表明,在未来6 h、12 h内的余水位的预测精度达到厘米级,在24 h内接近厘米级,证明了该组合模型在余水位短期预测方面的可行性。 相似文献
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龙口港极端设计水位的组合估计 总被引：1，自引：0，他引：1
传统的单因素极端设计水位计算方法忽略了天文潮位与风暴潮增水的联合作用.已经提出的天文潮与风暴潮增水的组合方法,也未能把二者当作相关的事件来考虑.选取龙口港连续25 a风暴潮增水和天文潮位资料,采用二维Log-normal理论分布进行计算,估计了多年一遇风暴潮增水与天文潮位的联合重现值,所得极端水位可供海岸防灾部门作为设计参考. 相似文献
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中国《海港水文规范》在确定港口工程设计潮位时,采用手绘累积频率曲线,再摘取设计潮位值的方法,由于缺乏理论曲线,确定的数值存在任意性。本文将改进最大熵分布应用于海岸港的设计高、低潮位的推算,计算精度高,克服了传统方法推算设计潮位值的不足,有重要理论与工程意义。 相似文献
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Water Level Retrieval Using SARAL/AltiKa Observations in the Braided Brahmaputra River,Eastern India
Amit Kumar Dubey Praveen Gupta Subashisa Dutta Raghvendra Pratap Singh 《Marine Geodesy》2015,38(3):549-567
In this study, water level retrieval over the Brahmaputra river was done using different retracking algorithms for the 40 Hz waveform data of SARAL/AltiKa satellite. Water level was retrieved at 10 different locations of the river to evaluate the performance and accuracy of Ka band altimeter over the braided river system. Different retracking algorithms such as ice-1, ice-2, threshold, and beta parameter were used to retrieve water levels. A correlation and error analysis between the in-situ and satellite altimetry derived river levels was carried out for all the stations. Performance and accuracy analysis has established that water level can be retrieved with less than 40 cm root mean square error (RMSE) for most of the braided reaches of the river. The statistical analysis have found that Beta parameter algorithm has performed best in most of the cases amongst the different retracking algorithms used in this study. The water levels derived from 10 different locations were used to generate water surface elevation profiles for the monsoon and nonmonsoon periods. The water levels and the water surface profiles derived from satellite altimetry indicate the potential use of altimeters for the parameterization and calibration of river hydrological, hydrodynamic and sediment transport models. 相似文献
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This paper presents the development of a Regional Neural Network for Water Level (RNN_WL) predictions, with an application to the coastal inlets along the South Shore of Long Island, New York. Long-term water level data at coastal inlets are important for studying coastal hydrodynamics sediment transport. However, it is quite common that long-term water level observations may be not available, due to the high cost of field data monitoring. Fortunately, the US National Oceanographic and Atmospheric Administration (NOAA) has a national network of water level monitoring stations distributed in regional scale that has been operating for several decades. Therefore, it is valuable and cost effective for a coastal engineering study to establish the relationship between water levels at a local station and a NOAA station in the region. Due to the changes of phase and amplitude of water levels over the regional coastal line, it is often difficult to obtain good linear regression relationship between water levels from two different stations. Using neural network offers an effective approach to correlate the non-linear input and output of water levels by recognizing the historic patterns between them. In this study, the RNN_WL model was developed to enable coastal engineers to predict long-term water levels in a coastal inlet, based on the input of data in a remote NOAA station in the region. The RNN_WL model was developed using a feed-forwards, back-propagation neural network structure with an optimized training algorithm. The RNN_WL model can be trained and verified using two independent data sets of hourly water levels.The RNN_WL model was tested in an application to Long Island South Shore. Located about 60–100 km away from the inlets there are two permanent long-term water level stations, which have been operated by NOAA since the1940s. The neural network model was trained using hourly data over a one-month period and validated for another one-month period. The model was then tested over year-long periods. Results indicate that, despite significant changes in the amplitudes and phases of the water levels over the regional study area, the RNN_WL model provides very good long-term predictions of both tidal and non-tidal water levels at the regional coastal inlets. In order to examine the effects of distance on the RNN_WL model performance, the model was also tested using water levels from other remote NOAA stations located at longer distances, which range from 234 km to 591 km away from the local station at the inlets. The satisfactory results indicate that the RNN_WL model is able to supplement long-term historical water level data at the coastal inlets based on the available data at remote NOAA stations in the coastal region. 相似文献
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夏季珠江冲淡水扩散路径分析 总被引：9，自引：0，他引：9
利用1978~1988年国家海洋局南海分局南海北部断面调查获得的盐度资料,分析了珠江口附近海域盐度的时空分布特征,描述了夏季珠江冲淡水的扩散路径。通过统计分析相应时间段的风场、平均海平面高度、珠江径流以及陆地降水等资料,讨论了影响珠江冲淡水扩散的主要因子。我们发现:夏季珠江冲淡水扩散方向与南风强度(频率和平均风速)、近岸海面月平均高度以及径流强度的关系极为密切,如果西南季风强盛,珠江冲淡水向东扩散就多;如果近岸海面高度显著增高,珠江冲淡水向西流动就特别强。 相似文献
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Hydrographic data collected from Gulf of Aden since 1920 have been compiled to identify and refine the definitions of water
masses in the Gulf of Aden (GA) and to describe their spatio-temporal variability. Four water masses have been identified
based on their θ-S characteristics. The Red Sea Water (RSW) that flows from the Red Sea is the most prominent water in the GA; this occupies
about 37% of the total volume of Gulf of Aden. The Gulf of Aden Surface Water (∼3%) forms as a mixture of local water and
the water from western Arabian Sea during winter and Red Sea surface water during summer. The intermediate water, identified
as Gulf of Aden Intermediate Water (GAIW), occupies about 9% of the total volume of GA; a characteristic salinity minimum
is associated with it at σθ=26.50 kg m−3. The northward spread of sub-tropical subsurface water from the south appears to be the major source of GAIW. The bottom
water, named Gulf of Aden Bottom Water, showed the least variability. It was formed due to the mixing of Red Sea Water and
water of southern origin. Mixing triangles have been used to analyze the composition of water in the GA. 相似文献
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1998年夏、冬季南海水团分析 总被引：15，自引：2，他引：15
为了解南海水团的特征和分布 ,基于 1 998年夏季和冬季两个航次的实测资料 ,采用聚类分析、判别分析和模糊分析方法 ,对南海的水团进行了分析。结果表明 ,南海外海水可划分为 6个水团 ,即南海表层水团、南海次表层水团、南海次 中层混合水团、南海中层水团、南海深层水团和南海底盆水。越南附近夏季存在一个暖涡 ;1 998年夏季还可鉴别出黑潮表层水团和黑潮次表层水团 ,但在冬季观测期间无黑潮水越过 1 1 9.5°E经线进入南海 ;这些现象可能与厄尔尼诺现象有关联。夏季有苏禄海海水在 5 0— 75m层经由民都洛海峡侵入南海 相似文献
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Takashi Yabuki Toshio Suga Kimio Hanawa Koji Matsuoka Hiroshi Kiwada Tomowo Watanabe 《Journal of Oceanography》2006,62(5):649-655
It has been inferred that the Prydz Bay region is one of the source regions of Antarctic Bottom Water (AABW) based on rather
indirect evidence. In order to examine this inference, we investigate the hydrographic condition of the bay based mainly on
XCTD data obtained during the Japanese Whale Research Program in the Antarctic (JARPA). The JARPA hydrographic data reveal
Circumpolar Deep Water (CDW), which is a salty, warm water mass approaching the shelf break, and capture Modified CDW (MCDW)
intruding into the shelf water. AABW production requires mixing of CDW and cold shelf water saltier than 34.6 psu, which is
a saltier type of Low Salinity Shelf Water (LSSW). Saltier LSSW is observed near the bottom over the shelf, being mixed with
MCDW. We further identify saltier LSSW near the shelf break. This saltier LSSW appears close enough to unmodified CDW to be
mixed with it over the continental slope, indicating a possible source of AABW in Prydz Bay. 相似文献
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Accurate water levels modeling and prediction is essential for safety of coastal navigation and other maritime applications. Water levels modeling and prediction is traditionally developed using the least-squares-based harmonic analysis method that estimates the harmonic constituents from the measured water levels. If long water level measurements are not obtained from the tide gauge, accurate water levels prediction cannot be estimated. To overcome the above limitations, the current state-of-the-art artificial neural network has recently been developed for water levels prediction from short water level measurements. However, a highly nonlinear and efficient wavelet network model is proposed and developed in this paper for water levels modeling and prediction using short water level measurements. Water level measurements (about one month and a week) from six different tide gauges are employed to develop the proposed model and investigate the atmospheric changes effect. It is shown that the majority of error values, the differences between water level measurements and the modeled and predicted values, fall within the −5 cm and +5 cm range and root-mean-squared (RMS) errors fall within 1–6 cm range. A comparison between the developed highly nonlinear wavelet network model and the harmonic analysis method and the artificial neural networks shows that the RMS of the developed wavelet network model when compared with the RMS of the harmonic analysis method is reduced by about 70% and when compared with the RMS of the artificial neural networks is reduced by about 22%. It is also worth noting that if the atmospheric changes effect (meteorological effect) of the air pressure, the air temperature, the relative humidity, wind speed and wind direction are considered, the performance accuracy of the developed wavelet network model is improved by about 20% (based on the estimated RMS values). 相似文献
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东海北部区域底层冷水团的形成及其季节变化 总被引：4，自引：1，他引：4
本文着重探讨东海北部底层冷水(北部冷水)的形成原因、基本特征和季节变化过程。指出北部冷水系冬季黄海沿岸水南下向东海输送低温水并与外海高盐水混合变性形成的。其位置随季节变化而有明显的移动规律,即先由西向东移,而后向北收缩。大体上可分为四个阶段:冷水舌离岸期,北部冷水半封闭期,北缩消亡期和更新期。文中分析了上述变化的原因,较详细地阐述了黄海沿岸水沿陆架下沉与黑潮次—中层混合水爬升的关系及其对北部冷水的影响。分析了北部冷水与黄海冷水团的关系。 相似文献