Stochastic bivariate time series models of waves in the North Sea and their application in simulation-based design

In this paper, we present and evaluate three long-term wave models for application in simulation-based design of ships and marine structures. Designers and researchers often rely on historical weather data as a source for ocean area characteristics based on hindcast datasets or in-situ measurements. The limited access and size of historical datasets reduces repeatability of simulations and analyses, making it difficult to assess the sampling variability of performance and loads on marine vessels and structures. Markov, VAR and VARMA wave models, producing independent long-term time series of significant wave height (H_s) and spectral peak period (T_p), is presented as possible solutions to this problem. The models are tested and compared by addressing how the models affect interpretation of design concepts and the ability to replicate statistical and physical characteristics of the wave process. Our results show that the VAR and VARMA models perform sufficiently in describing design performance, but does not capture the physical process fully. The Markov model is found to perform worst of the tested models in the applied tests, especially for measures covering several consecutive sea states.     

Obtaining the distribution of quiescent periods directly from the power spectral densities of Sea waves

There is a growing practical interest in the ability to increase the sea states at which marine operations can be safely undertaken by exploiting the quiescent periods that are well known to exist under a wide range of sea conditions. While the actual prediction of quiescent periods at sea for the control of operations is a deterministic process, the long term planning of future maritime tasks that rely on these quiescent periods is a statistical process involving the anticipated quiescence properties of the forecasted sea conditions in the geographical region of interest. It is in principle possible to obtain such data in tabular form either large scale simulation or from field data. However, such simulations are computationally intensive and libraries of appropriate field data are not common. Thus, it is clearly attractive to develop techniques that exploit standard wave spectral models for describing the quiescence statistics directly from such spectra. The present study focuses upon such techniques and is a first step towards the production of a computationally low-cost quiescence prediction tool and compares its efficacy against simulations. Two significant properties emerge for a large class of wave spectral models that encompasses the ubiquitous Neumann and Pierson Moskowitz or Bretschneider forms. Firstly, the auto-correlation function of the wave profile that are required to produce the quiescence property can be obtained analytically in terms of standard special functions. This considerably reduces the computational cost making desktop computer-based planning tools a reality. Secondly, for each class of these parametric spectra, the probability of a given number of consecutive wave heights (normalised to the significant wave heights) less than some critical value is in fact independent of absolute wave height. Thus, for a broad class of practically interesting wave spectra all that is required to obtain the statistical distribution of the quiescent periods is simple rescaling.     

A 10-year wave energy resource assessment and trends of Indonesia based on satellite observations

Wave energy resource assessment and trends around Indonesian's ocean has been carried out by means of analyzing satellite observations. Wave energy flux or wave power can be approximated using parameterized sea states derived from satellite data. Unfortunately, only some surface parameters can be measured from remote sensing satellites, for example for ocean surface waves: significant wave height. Others, like peak wave period and energy period are not available, but can instead be estimated using empirical models. The results have been assessed by meteorological season. The assessment shows clearly where and when the wave power resource is promising around Indonesian's ocean. The most striking result was found from June to August, in which about 30–40 kW/m(the 90 th percentile: 40–60 kW/m, the 99th percentile: 50–70 kW/m) wave power energy on average has been found around south of the Java Island. The significant trends of wave energy at the 95% level have also been studied and it is found that the trends only occurred for the extreme cases, which is the 99th percentile(i.e.,highest 1%). Wave power energy could increase up to 150 W/m per year. The significant wave heights and wave power have been compared with the results obtained from global wave model hindcast carried out by wave model WAVEWATCH III. The comparisons indicated excellent agreements.     

140kaBP以来南海西南部上升流影响区沉积记录及其古海洋环境变化

对南海西南部现代上升流区沉积物柱样BIS-187-61孔有机碳、生物蛋白石、碳酸盐等各沉积组分进行了详细的分析,试图探讨末次间冰期(MIS 5)以来南海西南部夏季上升流影响区沉积过程及其所反映的海洋环境变化过程。研究结果发现,140kaBP以来该孔沉积记录期总体表现为:碳酸盐百分含量冰期低间冰期高,主要受周边陆源物质输入稀释的控制,为典型的"大西洋型碳酸盐旋回",有机碳、生物蛋白石、碳酸钙以及陆源沉积物的堆积速率均在MIS 2期、MIS 4期和MIS 5e期出现高值。其中,MIS 2期和MIS 4期生源和陆源沉积堆积速率增加可能与冰期时冬季风增强及海平面下降导致陆源营养物质输入增加对初级生产力的刺激有关,也可能与陆源物质输入增加对海洋生源颗粒物输出的压载作用增强有关。而MIS 5e期南海海平面高度与现代相仿,间冰期较强的夏季风引起的越南沿岸上升流增强是导致该时段本研究区域表层初级生产力增强,沉积物总堆积速率及各组分堆积速率都相应增加的主要原因。     

面向中国洪涝灾害应急监测的无人机空港布局

当前洪涝灾害对社会的经济发展和人民生命财产安全构成严重威胁。无人机机动、灵活,安全性高,可迅捷甚至实时获取灾区影像,对灾情的快速评估和应急救援决策意义重大。遥感无人机在洪涝灾害救援中能够发挥的重要作用已得到广泛共识,但是由于灾害的突发性,缺乏就近部署的资源制约了无人机遥感观测和救援作用的发挥。针对突发灾害,在区域和全国范围内建立起一定的无人机遥感应急体系成为国家面向未来正在考虑的选项。基于此,本研究提出了基于中国科学院的野外台站构建全国无人机遥感观测网的设想。本研究以中国防范洪涝灾害等级分布数据、行政区划数据、中国科学院野外台站分布数据和当前无人机性能数据库为数据源;以行政区划离散并提取的中心点作为需求点,台站作为设施点,不同洪涝等级区域内需要无人机进行应急观测的重要程度作为权重,利用最大覆盖选址模型进行空港选址布局;利用成本-效益曲线确定台站的最佳数量,最终从268个台站中选取出81个作为支撑全国洪涝灾害无人机遥感观测网络的无人机空港。无人机空港布局结果在理论上能够实现对中国绝大数突发洪涝灾害在2 h内初步完成洪涝观测,这对于构建中国空天地一体化的洪涝灾害监测体系具有重要意义。同时,本研究中的方法和成果对于进一步构建行业和综合性的全国无人机遥感观测网也具有一定借鉴和参照意义。     

南海北部海域油气资源调查技术及其应用研究——震源子波检测及模拟分析

在野外采集中考察气枪的稳定性以及室内进行确定性子波反褶积处理,都要求能够获得气枪阵列的实时远场子波。从震源子波检测方法出发,阐述了近场子波采集、幅值转换及记录流程,并列举出实测近场子波时需要考虑解决的问题;接着介绍了震源远场子波的获取方法和主要途径;震源近场子波及远场子波的实测方案,检测震源子波所需的仪器设备和采集技术方法。文中分析了气枪子波的气泡干扰问题,虚反射与后续气泡震荡间的关系以及吸收衰减对子波的影响,并根据实测远场子波,对齐氏和范氏两种气体模型进行了模拟效果对比,结果表明:采用范氏气体模型所模拟的子波与实际子波更为吻合,模拟出的气枪的子波波形、振幅大小、气泡周期上,与业界通用的Nucleus软件的模拟结果吻合较好,在后续的使用中将继续优化。     

Impact of missing flow on active inundation areas and transformation of parafluvial wetlands in Punarbhaba–Tangon river basin of Indo-Bangladesh

Punarbhaba river of Indo-Bangladesh has experienced hydro-ecological alteration after installation of Komardanga dam in 1992 and consequently wetland and inundation areas have undergone into transformation. The present work intends to explore the impact of flow attenuation on contemporary and upcoming flood extent and flood plain wetlands. In post-dam condition, average and maximum flows are attenuated by 36 and 41%, respectively, and as a result the active flood prone area is squeezed considerably by 39.72%. Average flood water depth is also reduced by 37.87% (4.45metre) after flow modification. Due to shrinkages of flood prone areas, wetland area is also reduced from 215.70 to 90.40 km² and larger part of the present wetland area is under stress and critical state. Predicted flood prone areas in next 25 years will be 328.91 km² and consequently 65.63 km² wetland areas may further be under hydro-ecological threats. Release of ecological flow is essential to restore and preserve the wetland.     

基于Sentinel-1B SAR数据的洪水提取和监测

洪涝灾害是我国最严重的气象灾害之一,及时准确的洪灾监测是防灾减灾的重要前期工作和基础。本文利用sentinel-1B雷达数据,以黑瞎子岛为研究区,联合使用OSTU阈值分割法和随机森林面向对象分类法针对像素统计单波形、双波形、多波形SAR影像提取洪水要素,实现对洪灾淹没面积的时序监测,为灾情监测提供数据和技术支撑。     

1951—2018年衢州市椪柑采摘期连阴雨天气变化特征

基于1951—2018年衢州市椪柑采摘期降水量、雨日、日照时数、相对湿度等逐日气象资料,应用统计分析和小波分析方法,分析椪柑采摘期连阴雨天气变化特征及其大气环流背景.结果表明:1951—2018年衢州椪柑采摘期连阴雨日数、次数和强度呈略微增加趋势、滑动3d无雨次数呈减少趋势;滑动3d无雨次数存在明显的5a、7a和15a...     

长江-淮河流域短时暴雨洪涝灾害危险性预警评估及验证

洪涝灾害危险性预警分析是防灾减灾的重要基础,在灾害发生前进行预警,可以有效减轻灾害带来的影响。本文以2020年6—8月长江-淮河流域洪涝灾害为研究案例,首次利用前3天累计降水量(前期状态),当前时次土壤湿度(当前状态)和预测日降水量(未来状态)作为致灾因子,基于改进的层次分析法建立危险性预警分析模型。通过县域灾情信息验证表明,评估正确率达74.46%,遗漏率仅5.59%,评估结果与实际灾情吻合性好;同时对预警准确性和时相一致性进行评价,最大值(县内最高指数)的预警率达到81.6%;“特大型”暴雨洪涝灾害中的预警达到77.3%以上,且灾害在前3~5天危险性指数普遍提升,存在有效预警。本文方法对于长江—淮河流域短时暴雨洪涝灾害危险性预警有较好的准确性和可靠性,可提供防灾减灾决策依据。