黄渤海海域叶绿素a浓度时空特征分布及影响因子分析

本文基于2003-2017年黄渤海海域MODIS卫星遥感数据，利用自组织映射神经网络模型（SOM）研究了叶绿素a浓度（Chl-a）的典型分布模式，分析了Chl-a变化趋势，并利用广义加性模型（Generalized Additive Model ,GAM）研究其与环境因子的关系。结果表明：黄渤海Chl-a存在明显的季节性变化，7月份浓度最低2.41 mg·m-3, 4月份浓度最高3.43 mg·m-3； Chl-a呈现从近海岸海域向深水海盆逐渐降低的变化趋势；将SOM模型提取的典型模式分为清澈、低浓度、中浓度和高浓度模式，这些模式有效地阐明了2003-2017年黄渤海Chl-a在时间上存在春季高，夏季低的变化趋势，Chl-a高值区主要分布在河流的入海口及近海岸；利用GAM模型发现海表温度（SST）、风速（wind）与Chl-a之间存在显著的非线性关系，SST、wind对Chl-a变化的解释率39.3%，SST对Chl-a变化的影响比wind更大；人类活动的增加对黄渤海Chl-a变化也起着重要的作用。

Temporal-spatial distribution of chlorophyll-a and impacts of environmental factors in the Bohai Sea and Yellow Sea

In this study, the temporal and spatial distribution pattern of chlorophyll a concentration (Chl-a) derived from MODIS satellite data in the Bohai Sea and Yellow Sea during 2003 to 2017 and its relationship with environmental factors were studied based on the self-organizing map neural network model (SOM) and generalized additive model (GAM). The results showed distinct seasonal variations of Chl-a along with a gradual increase in the study period. Chl-a reached the lowest value of 2.41mg/m3 in July, and the highest value 3.43mg/m3 in April. The Chl-a decreased from the coast to deep water basin. The typical patterns extracted by SOM model are divided into clear, low concentration, medium concentration and high concentration modes, which effectively clarify that Chl-a in the Bohai Sea and Yellow Sea has high spring and low summer during 2003-2017 and the highest value area of Chl-a was mainly distributed in coastal estuaries. GAM was used to evaluate the effect of SST and wind on the changing of Chl-a, which found there is a significant nonlinear correlation between Chl-a and SST as well as wind speed. The interpretation rate of Chl-a change is 39.3%, and the effect of SST on Chl-a change is greater than that of wind. Human activities also plays an important role in the change of Chl-a in the Yellow Sea.