南黄海漂浮浒苔绿潮消亡时空变化特征研究
其他题名The spatiotemporal variation research of Ulva prolifera blooms dissipation in the Southern Yellow Sea
安德玉
学位类型博士
导师邢前国 研究员
2020-05
学位授予单位中国科学院大学
学位授予地点中国科学院烟台海岸带研究所
学位名称工学博士
学位专业环境科学
关键词绿潮云影响日消亡率变化时空变化沉降区分析
摘要绿潮的周期性暴发已成为南黄海海域严重的生态灾害之一，给沿海城市造成了巨大的社会经济损失。绿潮消亡后期，大量浒苔或登陆沿海地区，或沉入海底，在绿藻沉降分解的过程中会向海水释放大量的营养盐，改变水体理化环境，而绿潮的登陆过程则会对沿海地区的景观生态环境、人类生产活动等造成严重影响。因此，对于绿潮消亡过程应进行深入研究，了解其消亡规律，以期为评估其对海洋生态的影响及制定相应的绿潮防控策略提供理论依据。 基于2007—2019年MODIS影像和高分辨率影像（HJ-1A/1B、GF-1和Sentinel-2），本文首先针对影响绿潮面积估测的两个主要限制因素——云和空间分辨率，提出了相应的解决对策；在此基础上，分析了2007—2019年绿潮的日消亡率变化以及消亡期绿潮的时空变化特征，并初步推测了绿潮可能的沉降区域。主要结论如下： （1）云覆盖和空间分辨率会影响绿潮面积的估算。针对前者，本文基于云分布情况和云周围绿潮分布情况建立了云覆盖下绿潮面积估测方法。该方法在少云影像上的应用结果显示，2007—2019年间少云影像上估测的云覆盖下的绿潮面积占绿潮总面积的百分比（P_cloud_GT）介于0.47%~28.17%。针对后者，本文基于同期多源卫星影像，给出了两种解决对策。一是分别建立了多源卫星影像绿潮面积（Area）转换关系模型。应用模型后，GF-1和Sentinel-2、HJ-1A/B上对应斑块的面积偏差分别从22.77%和36.40%降低到14.44%和24.38%；MODIS与Sentinel-2、GF-1、HJ-1A/1B影像上对应斑块的面积偏差分别从229.09%、153.06%和89.17%降低到23.97%、18.69%和23.25%。二是给出了低空间分辨率影像的绿潮亚像元面积（ACCM）估测模型，应用模型后，MODIS与高分辨影像估测的ACCM相对误差最大为13.59%，远小于Area的相对误差（最小为55.85%）。 （2）通过两个相邻日期之间的日消亡率（TND）和从不同开始日期到最小面积日期的日消亡率（DSE）分析了2007—2019年绿潮的日消亡率。除2010年外，DSE年内变化较为一致，均呈增加趋势；TND年内变化差异较大。年际尺度上，DSE、TND最大值与绿潮最大面积的整体趋势较为一致，均呈现增加趋势，R2分别为0.60、0.41和0.34。基于2007—2017年绿潮的日消亡率变化，提出了预估绿潮消亡天数的方法。该方法应用于2018年和2019年的结果显示，消亡天数的预估值和实际值较为接近，尤其是2018年，两者的相对误差仅为6.67%。 （3）从两个方面分析了绿潮消亡的时空变化特征，一是绿潮在山东半岛南部的登陆顺序变化，二是绿潮对南黄海不同区域的影响程度变化。结果显示，绿潮的登陆顺序存在差异，大致可分为两类：一是日照→青岛→乳山、海阳，二是乳山、海阳→青岛→日照。绿潮对南黄海区域的影响程度存在空间差异，影响最为严重的区域位于34o50'N~36o1'N，120o32'E~121o33'E海域内。其中，对山东半岛南部海域影响最为严重的区域为青岛近岸海域，最轻的区域是乳山近岸海域。基于绿潮时空变化推测可能的绿潮沉降区分别是山东半岛近岸海域和南黄海中部33o31'N~35o22'N，120o14'E~122o8'E海域。
其他摘要The periodic outbreak of green tide has become one of the most serious ecological disasters in the southern Yellow Sea, causing huge social and economic losses to the coastal regions. In the later stage of green tide dissipation, large amounts of Ulva prolifera was either landing in coastal regions, or sinking into the sea. Abundant types of nutrients will be released into the sea during the decomposition of green tide, altering the physical-chemical environment of the sea water. In addition, the landing of green tide will lead to serious impacts on the landscape ecological environment and human activities in coastal regions. Therefore, further studies should be conducted on the dissipation of green tide to clarify its dissipation characteristic, so as to provide theoretical basis for evaluating its impact on marine ecology and formulating the corresponding green tide prevention and control strategies.Multiple satellite data including MODIS, HJ-1A/1B, GF-1 and Sentinel-2 during the period from 2007 to 2019 were used in this study. Firstly, the solutions were proposed to improve the accuracy of the estimation area of the green tide limited by the cloud and spatial resolution. Then, the daily dissipation rate and spatiotemporal variation of green tide were analyzed based on the monitoring results of remote sensing image. Finally, the possible deposition regions were preliminarily speculated. The main conclusions are as follows:(1) Cloud cover and spatial resolution affect the estimation accuracy of green tide. To eliminate the impact of cloud, a method for estimating the green tide area under cloud was proposed based on cloud and green tide distribution. The percentage of the green tide area covered by the cloud (P_cloud_GT) ranged between 0.47% and 28.17% to the total green tide area during the period from 2007 to 2019. To reduce the impact of spatial resolution, based on semi-simultaneous multi-source images, two solutions were proposed. The first one is that we constructed transformation models of green tide areas (Area) estimated by multi-source images. Applying these models, the relative deviations of corresponding patch area from GF-1, Sentinel-2 and HJ-1A/B images decreased from 22.77% and 36.40% to 14.44% and 24.38%, respectively. The relative deviations of corresponding patch area from MODIS and Sentinel-2, GF-1 and HJ-1A/1B images decreased from 229.09%, 153.06% and 89.17% to 23.97%, 18.69% and 23.25%, respectively. The second one was that we proposed a green tide sub-pixel coverage (ACCM) estimation model to reduce the impact of coarse spatial resolution. Applying this model, the maximum relative error of ACCM between MODIS and high-resolution image was 13.59%, which was much smaller than the relative error of Area (the minimum is 55.85%).(2) The daily dissipation rate (DR) of green tide during the period from 2007 to 2019 was analyzed from two aspects. One was the DR between two neighboring dates (TND), and the other was the DR from different starting dates to the minimum area date (DSE). It is found that the DSE exhibits an increasing trend within a year (except 2010), while the TND show much difference for different year. In interannual scale, the overall trend of the maximum of DSE and TND is increasing, which is consistent with the maximum of green tide area, with the corresponding R2 of 0.60, 0.41 and 0.34, respectively. A prediction method of the green tide dissipation duration has been proposed based on the daily dissipation rate variation during the period from 2007 to 2017. When using this method to 2018 and 2019, the predicted values were very close to the actual values, especially in 2018 where the relative error between them was only 6.67%.(3) The dissipation characteristic of green tide during the period from 2007 to 2019 were analyzed from two aspects. One was the landing sequence of green tide in the southern part of Shandong Peninsula, and the other was the distribution density of green tide in the southern Yellow Sea. Two types of landing sequence were found. One type was following the order of Rizhao, Qingdao, Rushan and Haiyang, the other type was in the reverse order. The distribution density of green tide had significant differences in the southern Yellow Sea. The most seriously affected region was mainly located in the area of 34o50'N~36o1'N, 120o32'E~121o33'E. While concerned in southern Shandong Peninsula coastal water, the most seriously affected region was coastal water near Qingdao, while the lightest affected region was coastal water near Rushan. Based on the dissipation characteristic of green tide, it can be speculated that the coastal regions of Shandong peninsula and the center of southern Yellow Sea(33o31'N ~ 35o22' N, 120o14 'E ~ 122o8' E) were most likely to the possible deposition regions of green tide.
语种中文
文献类型学位论文
条目标识符http://ir.yic.ac.cnhttp://ir.yic.ac.cn/handle/133337/24216
专题中科院烟台海岸带研究所知识产出_学位论文

推荐引用方式
GB/T 7714安德玉. 南黄海漂浮浒苔绿潮消亡时空变化特征研究[D]. 中国科学院烟台海岸带研究所. 中国科学院大学,2020.


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