基于卫星观测及水质动力模型的感潮河流水质监测分析

Water quality analysis of tidal river based on satellite observation and dynamic model

综合高分辨率卫星观测具有时空连续覆盖和水质动力模型具有高时间分辨率的优势,对感潮河段的水质进行监测。通过Lansat8/OLI卫星数据定量反演了感潮河段-黄浦江的叶绿素a质量浓度,反演结果与地面实测数据的均方根误差为4.82 mg·m^(-3),决定系数R2为0.68。通过水质动力模型Delft3D,模拟了黄浦江水质参数(溶解氧(DO)、氨氮(NH3-N)和高锰酸钾指数(CODMn))。结果表明:模拟水位与实测水位的均方根误差为0.22 m;水质参数DO、NH_(3)-N、COD_(Mn)的验证均方根误差分别为0.53、0.16、0.27 mg·L^(-1)。进一步分析后发现,2013年8月—2014年7月随着黄浦江叶绿素a质量浓度的增大,DO与NH_(3)-N也相应增大,CODMn则相应减小。通过叶绿素a质量浓度与水质参数所构建的关系式,利用Lansat8/OLI卫星数据反演了不同时期的黄浦江DO、NH_(3)-N、COD_(Mn),发现感潮河段水质参数存在季节性变化。卫星观测与水质动力模型相结合的方法可为海岸带感潮河流时空快速变化的水质监测提供参考。

The advantages of continuous space-time coverage by satellite observations and high time resolution by water quality and hydrodynamic models were complemented and utilized in this study to analyze the water quality change of the tidal river. Based on the in-situ data, the chlorophyll a concentration of the tidal riverHuangpu River was quantitatively retrieved by Lansat8/OLI satellite data. The root mean square error between the inversion data and the measured data was 4.82 mg·m^(-3), and the determination coefficient R2 was 0.68. Based on the Delft3 D model, the water quality parameters of the Huangpu River Dissolved, i.e. Oxygen(DO),Ammonia Nitrogen(NH_(3)-N) and Potassium Permanganate Index(CODMn), were simulated. Results showed that the root mean square error of the simulated water level by the hydrodynamic module was 0.22 m, and the verified root mean square errors of DO, NH_(3)-N, and CODMn were 0.53 mg·L^(-1), 0.16 mg·L^(-1), 0.27 mg·L^(-1),respectively. The correlation between chlorophyll a concentration and water quality parameters of Huangpu River from August 2013 to July 2014 was further analyzed. It was found that with the increase of chlorophyll a concentration in Huangpu River, DO and NH3-N increased while CODMn decreased. Based on the correlation between chlorophyll-a concentration and water quality parameters, the DO, NH_(3)-N, and CODMn of Huangpu River were retrieved by using Lansat8/OLI satellite data. It was found that the water quality parameter values varied greatly with seasons for tidal river. This study demonstrated the great significance to combine satellite observation with dynamic model for water quality analysis of tidal rivers.