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基于Landsat遥感数据的田湾核电站温排水时空特征研究
引用本文:邢梦玲,王迪峰,何贤强,白雁,成印河.基于Landsat遥感数据的田湾核电站温排水时空特征研究[J].海洋学研究,2020,38(4):72-79.
作者姓名:邢梦玲  王迪峰  何贤强  白雁  成印河
作者单位:1.江苏海洋大学 测绘与海洋信息学院,江苏 连云港 222005; 2.卫星海洋环境动力学国家重点实验室,浙江 杭州 310012; 3.自然资源部 第二海洋研究所,浙江 杭州 310012
基金项目:浙江省重点研发计划(2017C03037);国家重点研发计划(2018YFB0505005,2017YFC140 5300);国家自然科学基金(41476157,41776029,L1624046)
摘    要:本文基于2007—2018年Landsat系列遥感卫星数据开展田湾核电站温排水时空变化特征及其影响分析。采用辐射传输方程算法和劈窗算法对核电站周围海域的海表温度进行反演,通过星星匹配对反演温度的精度进行验证。匹配验证结果表明,反演的Landsat海表温度与MODIS海表温度产品具有较好的一致性,决定系数达到0.91。基于研究海域温度反演结果分析了核电站温排水面积的季节变化、年际变化和潮周期内变化特征,并且分析了潮汐与风场对温排水扩散的影响。结果表明,核电站周边海域各季节的温升区面积存在明显差异,春季最大,可达秋季的7倍;2007—2018年,随着装机容量的扩大,温排水面积不断扩大,2018年达到峰值,瞬时最大面积可达101.7 km2;潮汐对温排水扩散有影响,涨憩时刻温升区面积较落憩时刻大;有利风会促进温排水扩散,但影响有限。

关 键 词:温排水  长时间序列  时空特征  Landsat  
收稿时间:2020-08-30

Temporal and spatial characteristics of thermal discharge in Tianwan Nuclear Power Plant based on remote sensing data
XING Mengling,WANG Difeng,HE Xianqiang,BAI Yan,CHENG Yinhe.Temporal and spatial characteristics of thermal discharge in Tianwan Nuclear Power Plant based on remote sensing data[J].Journal of Marine Sciences,2020,38(4):72-79.
Authors:XING Mengling  WANG Difeng  HE Xianqiang  BAI Yan  CHENG Yinhe
Affiliation:1. School of Marine Technology and Geomatics, Jiangsu Ocean University, Lianyungang 222005, China; 2. State Key Laboratory of Satellite Ocean Environment Dynamics, Hangzhou 310012, China; 3. Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China
Abstract:Based on 2007-2018 Landsat series of multi-source remote sensing satellite data, the spatial-temporal characteristics and affecting analysis were carried. The radiative transfer equation algorithm and split-window algorithm were used to retrieve sea surface temperature. After verifying the algorithm through Landsat-MODIS comparison, it shows that the inversed results have a significant linear correlation with the MODIS SST products. Based on the temperature retrieve results of the study area, the characteristics of the seasonal, annual and tidal variation were analyzed. In the aspect of seasonal distribution, the range of spring thermal discharge which is the largest in four seasons is 7 times of autumn one. In the aspect of interannual distribution, with the expansion of installed capacity, the range of thermal discharge continues to expand, reaching to the peak in 2018. In terms of the influence of tides on thermal discharge, the thermal discharge at the moment of high water slack is larger than that of the low water slack. West wind is beneficial to the diffusion of thermal discharge, but its impact on thermal discharge is limited.
Keywords:thermal discharge  long time series  spatial-temporal characteristics  Landsat  
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