利用HY-1C卫星CZI数据在COVID-19疫情期间武汉知音湖和黄家湖的浊度监测研究

Water Turbidity Monitoring of Zhiyin and Huangjia Lakes in Wuhan for COVID-19 Epidemic Using HY-1C CZI Data

  • 摘要: 水体浊度是内陆湖泊水质的重要参数之一,是水环境生态系统中重要的影响因子。2019年12月底,武汉市受到新型冠状病毒肺炎疫情的影响,政府在2020-01-25—2020-02-05期间紧急建设了火神山和雷神山医院。医院建设过程中,对附近水体浊度进行动态监测有助于疫情防控与政府决策。以我国较高空间分辨率的水色海洋1C(Haiyang-1C,HY-1C)卫星海岸带成像仪(coastal zone imager,CZI)传感器数据为基础,结合高频同步浊度自动监测站测量数据,利用全局半经验浊度反演算法,建立了适用于武汉水体的浊度反演模型。利用该模型分析了医院建设前、中、后期的知音湖、黄家湖和朱山湖遥感反演的水体浊度变化,发现医院附近的水体与远离医院的水体浊度变化趋势一致,说明医院的建设施工不是影响浊度变化的原因;同时分析了武汉的降雨在医院建设前、中、后期的变化,发现降雨量的变化可能是导致水体浊度下降的主要因素。该研究也表明,国产较高分辨率水色遥感HY-1C卫星CZI传感器具有良好的小型内陆水体浊度动态监测能力。

     

    Abstract: Water turbidity is one of the most important parameters of inland lake water quality and an important influencing factor of water environment ecosystem.Affected by coronavirus disease 2019(COVID-19) epidemic, during the period from January 25, 2020 to February 5, 2020, Wuhan government built two emergency hospitals, namely Huoshenshan Hospital and Leishenshan Hospital, to cope with the epidemic. In the process of hospital construction, dynamic monitoring of turbidity in the adjacent waters is helpful for epidemic prevention and government decision-making. Using Chinese high-resolution Haiyang-1C (HY-1C) coastal zone imager (CZI) data, combined with high-frequency in-situ turbidity measurements, a turbidity model uitable for Wuhan waters is established (determinant coefficient: R2>0.85; root mean square error: RMSE < 5.50 NTU). Through the analysis of the variations of turbidity at Zhiyin, Huangjia, and Zhushan lakes before, during, and after constructions of Huoshenshan or Leishenshan hospitals, we find out that the variation trends of waters near and away from Huoshenshan or Leishenshan hospitals are similar, which indicates that the constructions of the two hospitals doesn't affect the nearby waters. This study also shows that Chinese HY-1C CZI has the potential to retrieve turbidity in small inland waters.

     

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