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71.
Jiezhong Wu Nengwang Chen Huasheng Hong Ting Lu Longjian Wang Zhuhong Chen 《Marine pollution bulletin》2013,66(1-2):125-134
The spatial pattern and seasonal variation of denitrification were investigated during 2010–2011 in the Jiulong River Estuary (JRE) in southeast China. Dissolved N2 was directly measured by changes in the N2:Ar ratio. The results showed that excess dissolved N2 ranged from ?9.9 to 76.4 μmol L?1. Tidal mixing leads to a seaward decline of dissolved gaseous concentrations and water–air fluxes along the river-estuary gradient. Denitrification at freshwater sites varied between seasons, associated with changes in N input and water temperature. The denitrification process was controlled by the nitrate level at freshwater sites, and the excess dissolved N2 observed at the tidal zone largely originated from upstream water transport. Compared to other estuaries, JRE has a relative low gaseous removal efficiency (Ed = 12% of [DIN]; annual N removal = 24% of DIN load), a fact ascribed to strong tidal mixing, coarse-textured sediment with shallow depth before bedrock and high riverine DIN input. 相似文献
72.
声波测井曲线在地震反演中起着约束和控制模型反演的作用,当其不能反映地层岩性变化时,通常会将现有的非声波测井曲线按照一定的经验公式或统计方法来重构新的声波曲线。但是,这些拟声波曲线构建技术并没有考虑到地层岩石孔隙及孔隙中流体的影响。在考虑到岩石孔隙和孔隙中流体的情况下,拟声波曲线构建技术可以先利用岩石基质的声波速度与自然伽马之间的关系来重构具有声波量纲的新曲线,然后结合原声波曲线中能够反映背景速度的低频信息,构建出新的声波曲线。该方法在鄂尔多斯盆地镇泾地区取得了不错的应用效果。 相似文献
73.
74.
基于最大相关最小冗余度算法和随机森林回归算法,该文提出一种对欧洲中期天气预报中心(ECMWF)集合预报产品进行暴雨预报的释用方法。该方法采用最大相关最小冗余度算法,对ECMWF集合预报的51个成员进行筛选,选取若干个与预报对象相关性最大、相互间冗余度最小的成员作为随机森林回归算法的输入因子。利用ECMWF集合预报降水量平均值对建模样本进行分类,使预报模型的建模样本更具有针对性。通过2012年4月—2015年12月的交叉独立样本试验预报和2016年1—9月的业务预报试验的统计结果表明:该释用方法的暴雨预报TS和ETS评分,均比采用ECMWF集合预报产品51个成员降水量预报进行插值后取平均值的释用方法分别提高了0.07和0.05以上,显示了较好的数值预报产品释用效果。 相似文献
75.
76.
Zhang Zhenchang Hong Huasheng Wai Onyx Winghong Jiang Yuwu Zhou Changle 《中国海洋湖沼学报》2010,28(6):1340-1349
We enhance a robust parallel finite element model for coasts and estuaries cases with the use of N-Best refinement algorithms,
in multilevel partitioning scheme. Graph partitioning is an important step to construct the parallel model, in which computation
speed is a big concern. The partitioning strategy includes the division of the research domain into several semi-equal-sized
sub-domains, minimizing the sum weight of edges between different sub-domains. Multilevel schemes for graph partitioning are
divided into three phases: coarsening, partitioning, and uncoarsening. In the uncoarsening phase, many refinement algorithms
have been proposed previously, such as KL, Greedy, and Boundary refinements. In this study, we propose an N-Best refinement
algorithm and show its advantages in our case study of Xiamen Bay. Compared with original partitioning algorithm in previous
models, the N-Best algorithm can speed up the computation by 1.9 times, and the simulation results are in a good match with
the in-situ data. 相似文献
77.
78.
提出一种新的外部扰动场赋值的建模方法。该方法将场赋值问题纳入统一引力场表示理论的框架,得到的模式具有结构简单、奇性弱的核,并顾及了地形效应,适合低空引力速算。 相似文献
79.
80.
Jianyu Hu Hiroshi Kawamura Chunyan Li Huasheng Hong Yuwu Jiang 《Journal of Oceanography》2010,66(5):591-610
Patterns and features of currents and seawater volume transports in the Taiwan Strait have been reviewed by examining the results from more than 150 research papers in recent decades. It is noted that there are diverse or even conflicting viewpoints on these subjects. Here both common and different opinions are summarized. This review paper covers the studies involving in situ measurements and numerical modeling of current velocity, analyses of hydrographic data, and classification of water masses. Generally speaking, there are three currents in the Taiwan Strait: the China Coastal Current along the Fujian coast in the western Taiwan Strait, the extension of the South China Sea Warm Current in the western and central Taiwan Strait, and the Kuroshio’s branch or loop current intruding through the eastern Taiwan Strait. The current pattern in winter is quite different from that in summer, and the currents also exhibit differences between the upper and lower layers. The seawater volume transport through the Taiwan Strait is about 2.3 Sv northward in summer but about 0.8 Sv northward in winter. Both the current pattern and the seawater transport vary with local winds in the Taiwan Strait. This is particularly true in winter when the currents and the transport in the upper layer are significantly affected by strong northeasterly winds. 相似文献