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鄱阳湖现有水环境监测点时空分布特征分析 被引量:3
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作者 陈明华 刘恋 葛刚 《水文》 CSCD 北大核心 2019年第4期29-33,11,共6页
水环境监测布点的科学性直接影响水环境评价,如何评价鄱阳湖水环境现状和演化趋势,在时间、空间和频次上构建科学合理的时空监测体系是评价鄱阳湖水环境健康的关键。通过分析环保、水利和科研院所等单位现有的布点和监测数据,鄱阳湖水... 水环境监测布点的科学性直接影响水环境评价,如何评价鄱阳湖水环境现状和演化趋势,在时间、空间和频次上构建科学合理的时空监测体系是评价鄱阳湖水环境健康的关键。通过分析环保、水利和科研院所等单位现有的布点和监测数据,鄱阳湖水环境监测布点应按以下原则设定:(1)鄱阳湖水环境全年应设监测点35个,监测断面29个;(2)鄱阳湖采样时间频率上至少每月一次,具体采样时间避开采砂等人类生产活动的影响,采样时间一般定在每月下旬,且在采样当天前5d没有下雨且透明度在30 cm以上;(3)鄱阳湖空间异质性高,水质监测需分区采样,监测点的水质数据仅代表分区水质状况;(4)鄱阳湖需逆水流方向采样,确保采集不同水样;(5)鄱阳湖水环境监测需与水文监测同步进行,监测指标至少不能少于常规监测的营养盐及物理参数等。 展开更多
关键词 鄱阳湖 水环境 水文 时空布点
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Spatiotemporal features and possible mechanisms of seasonal changes in sea surface height south of Japan
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作者 马利斌 《Chinese Journal of Oceanology and Limnology》 SCIE CAS CSCD 2014年第4期933-945,共13页
Variations of sea surface height (SSH) in the Kuroshio south of Japan are addressed by analyzing 19-year (1993-2011) altimetry data from AVISO. Regionally averaged time series of observed SSH had a rising linear t... Variations of sea surface height (SSH) in the Kuroshio south of Japan are addressed by analyzing 19-year (1993-2011) altimetry data from AVISO. Regionally averaged time series of observed SSH had a rising linear trend at 2.64+0.72 mrn/a in this period. By analyzing the power spectra, several periods were recognized in temporal SSH variations, including those around 90 and 360 days. The seasonal cycle of SSH was minimum in winter (February) and maximum in summer (August), with peak-to-peak amplitude about 20.0 cm. The spatial distribution of linear trends was inhomogeneous, with a rising linear trend along the coastline and a tripole structure offshore. Spatial distributions of standard deviation of seasonal SSH show very dynamic activities in the southeast of Kyushu and south of Honshu. Seasonal variations of observed SSH are partially explained by surface buoyancy forcing, local wind forcing and the steric component related to subsurface water beneath the mixed layer. Results show different spatial distributions of correlation coefficient and estimation skill between seasonally observed and modeled SSH, which are calculated from surface buoyancy flux, local wind forcing and the steric component related to subsurface water. Of those three, the surface buoyancy flux has a greater contribution to variations of observed SSH on the seasonal time scale south of Japan. 展开更多
关键词 spatiotemporal variation net surface heat flux wind stress subsurface water
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