Long-Term Satellite Observations of Microcystin Concentrations in Lake Taihu during Cyanobacterial Bloom Periods.
Long-Term Satellite Observations of Microcystin Concentrations in Lake Taihu during Cyanobacterial Bloom Periods.
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DOI：
10.1021/es505901a
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发表时间：
2015-05
影响因子：
11.4
通讯作者：
Kun Shi;Yunlin Zhang;Hai Xu;G. Zhu;B. Qin;Changchun Huang;Xiaohan Liu;Yongqiang Zhou;Heng Lv-Heng
中科院分区：
文献类型：
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作者：
Kun Shi;Yunlin Zhang;Hai Xu;G. Zhu;B. Qin;Changchun Huang;Xiaohan Liu;Yongqiang Zhou;Heng Lv-Heng
蓝藻产生的微囊藻毒素对公众健康构成严重威胁。因此，淡水中微囊藻毒素分布的情报对环境机构、水资源管理机构和公共卫生组织至关重要。我们开发并验证了一个经验模型，以量化MCs在太湖蓝藻水华期间使用大气瑞利校正的中分辨率成像光谱仪（MODIS-Aqua）（Rrc）产品和原位数据的叶绿素a浓度（Chla）。首先，在MCs和Chla之间（r = 0.91; p < 0.001; t检验）以及Chla和来自Rrc的光谱指数之间（r = -0.86; p < 0.05; t检验）构建了稳健的关系。然后，结合这两种关系，构建了一个分析太湖MCs的区域算法。该模型进行了验证，然后应用到一个11年的系列的MODIS-Aqua数据调查MCs的时空分布。湖泊中的MCs在空间和时间上都有明显的变化。蓝藻水华、蓝藻浮渣、温度、风力和光照等因素可能影响太湖微囊藻的时空分布。研究结果表明，遥感侦察结合原位监测可以大大有助于淡水MCs的评估。
Microcystins (MCs) produced by cyanobacteria pose a serious threat to public health. Intelligence on MCs distributions in freshwater is therefore critical for environmental agencies, water authorities, and public health organizations. We developed and validated an empirical model to quantify MCs in Lake Taihu during cyanobacterial bloom periods using the atmospherically Rayleigh-corrected moderate resolution imaging spectroradiometer (MODIS-Aqua) (Rrc) products and in situ data by means of chlorophyll a concentrations (Chla). First, robust relationships were constructed between MCs and Chla (r = 0.91; p < 0.001; t-test) and between Chla and a spectral index derived from Rrc (r = -0.86; p < 0.05; t-test). Then, a regional algorithm to analyze MCs in Lake Taihu was constructed by combining the two relationships. The model was validated and then applied to an 11-year series of MODIS-Aqua data to investigate the spatial and temporal distributions of MCs. MCs in the lake were markedly variable both spatially and temporally. Cyanobacterial bloom scums, temperature, wind, and light conditions probably affected the temporal and spatial distribution of MCs in Lake Taihu. The findings demonstrate that remote sensing reconnaissance in conjunction with in situ monitoring can greatly aid MCs assessment in freshwater.