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巢湖2016年蓝藻水华时空分布及环境驱动力分析
摘要点击 158  全文点击 83  投稿时间:2018-01-05  修订日期:2018-04-22
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中文关键词  巢湖  蓝藻水华  时空分布  气象因子  环境驱动力
英文关键词  Lake Chaohu  floating algal blooms  spatial and temporal dynamics  meteorological factors  environmental drivers
作者单位E-mail
胡旻琪 中国科学院南京地理与湖泊研究所, 湖泊与环境国家重点实验室, 南京 210008
中国科学院大学, 北京 100049 
huminqi28@163.com 
张玉超 中国科学院南京地理与湖泊研究所, 湖泊与环境国家重点实验室, 南京 210008 yczhang@niglas.ac.cn 
马荣华 中国科学院南京地理与湖泊研究所, 湖泊与环境国家重点实验室, 南京 210008  
张壹萱 中国科学院南京地理与湖泊研究所, 湖泊与环境国家重点实验室, 南京 210008
中国科学院大学, 北京 100049 
 
中文摘要
      针对近年来巢湖蓝藻水华暴发频繁,基于中分辨率成像光谱仪(moderate-resolution imaging spectrum-radiometer,MODIS)多光谱遥感数据,采用浮游藻类指数(floating algae index,FAI)和藻华像元生长算法(algae pixel-growing algorithm,APA)提取了巢湖蓝藻水华覆盖面积,在分析2016年巢湖蓝藻水华时空分布规律基础上,结合巢湖水质、气象数据,讨论了藻华暴发的主要环境驱动力.结果表明,2016年巢湖藻华暴发季节与往年一致(5~11月),但藻华首次暴发时间推迟到5月,持续时间缩短至204 d,平均藻华面积85.53 km2.其环境驱动力研究发现,尽管巢湖主要水质指标呈现下降趋势,但总氮、总磷浓度依然分别超过V类和IV类水质标准;与往年相比,2016年春季风速偏大(△W=0.1 m·s-1)、降水偏多(△P=0.8 mm)与日照时数偏低(△S=-1.3 h)是巢湖藻华面积减少、起始暴发时间推迟的主要原因;藻华持续期内,降水成为影响藻华面积月际变化的主要影响因素,当日平均风速不仅与当天藻华面积存在较显著的负相关(P<0.05),当风速较大时对后续几日的藻华面积产生一定的滞后影响.这些研究结果有助于了解巢湖蓝藻水华情况,为应对巢湖藻华暴发与气候变化提供理论依据.
英文摘要
      Lake Chaohu has drawn increasing attention due to the occurrence of massive algal blooms. This study applied daily monitoring results from moderate-resolution imaging spectrum-radiometer (MODIS) satellite to extract algal blooms with a floating algal index algorithm and characterize surface floating algal bloom dynamics in 2016 with an algae pixel-growing algorithm. Combining water quality and meteorological data, environmental driving forces of algal blooms in 2016 were explored. The results showed that cyanobacterial blooms occurred throughout the lake from May to November, which is the same as in previous years. Compared with previous years, the initial bloom date was postponed to May, the duration was reduced to 204 days, and the average floating algal bloom area was reduced to 85.53 km2. By investigating the environmental driving forces affecting the algal bloom, it was found that a larger wind speed (△W=0.1 m·s-1), more precipitation (△P=0.8 mm), and a lower sunshine duration (△S=-1.3 h) in spring were the main reasons. When the temperature was suitable, precipitation was the main driving force affecting the monthly variation in algal blooms. The daily average wind speed was also negatively correlated with the algal bloom area (P<0.05). High wind speed can affect the area of algal blooms as well. These results will aid understanding of the situation of cyanobacterial blooms in Lake Chaohu and provide a theoretical basis for dealing with algal blooming and climate change.

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