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长江河口动量系数时空变化规律研究

Temporal and spatial variation law of momentum coefficients in the Yangtze Estuary
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摘要 利用近期实测资料,对长江河口肖山—口门区域的动量系数进行时间和空间分布规律研究;在此基础上,得出动量系数边滩和深槽分布的差异性,并建立了经验曲线.主要结论:动量系数近口段和河口段一般为洪季大于枯季,但北槽进口枯季大于洪季;洪季肖山—石化下大潮大于小潮,枯季时肖山—狼山沙为大潮大于小潮,徐六泾—石化下为大潮小于小潮;洪季以潮流界作为界限,潮流界以下向海方向动量系数表现为增加趋势;在空间上,北港大于南港,北槽大于南槽;引起这一差异的主要原因为不同时间和空间径流和潮流水动力差异所致.以-15 m水深划分近口段边滩和深槽,边滩区域动量系数随水深增大而增加,深槽区域动量系数变化不大. Based on the measured data of Xiaoshan to Yangtze Estuary reach,the temporal and spatial distribution law of momentum coefficients was studied.Then the difference of coefficients in beaches and deep trough was obtained and the empirical curve was established.The results showed that the momentum coefficients in wet seasons were higher than that in dry seasons in the estuary,while the law was totally contrary in the North Passage.The coefficients in spring tidal were higher than those in neap tidal from Xiaoshan to Shihuaxia in wet seasons.In dry seasons, the coefficients in spring tidal were higher than those in neaps tidal from Xiaoshan to Langshashan and the law was contrary from Xuliujing to Shihuaxia.The tidal limit was the boundary that the downstream coefficients of it were increasing.The coefficients in North Channel were higher than those in South Channel and the coefficients in North Passage were higher than those in South Passage.The main reason of this phenomenon was the temporal and spatial variation of driving forces of runoff and tide.The water depth of 15 m was thinking as the demarcation of point bars and deep troughs.The momentum coefficients increased with the increase of the water depth in the point bars and the coefficients didn't change much in the deep troughs.The empirical curve was also established.
出处 《华东师范大学学报(自然科学版)》 CAS CSCD 北大核心 2013年第5期9-17,共9页 Journal of East China Normal University(Natural Science)
基金 国家重点基础研究发展计划(973计划)(2010CB429002) 武汉大学创新项目(2012206020212)
关键词 长江河口 动量系数 时空分布 滩槽分布 经验曲线 Yangtze Estuary momentum coefficient temporal and spatial distribution distribution of beach and deep trough experience curve
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