天空地一体立体网络的水质遥感监测及其溯源初探——以淀山湖为例

Stereoscopic Network Monitoring for Water Quality Integration of Satellite,UAV,and Ship Observations:A Case Study of Dianshan Lake

利用卫星遥感、无人机和走航船等手段组成的天空地一体化立体水质监测网络对淀山湖水质进行监测,并对水质参数的空间分布进行溯源分析。结果表明:(1)构建的水质参数反演模型实现了对淀山湖区域高精度的水质反演。其中总磷质量浓度反演结果的均方根误差(RMSE)为0.0191 mg/L,决定系数(R^(2))=0.64(P<0.001);氨氮质量浓度反演结果的RMSE为0.0360 mg/L,R^(2)=0.83(P<0.001);(2)水质空间分布特征为淀山湖总磷和氨氮浓度均表现为西北高,中部和东西低;叶绿素a浓度呈现出北高南低、东高西低及岸边高、中心低的空间分布特征;(3)通过广义线性混合模型对淀山湖水质空间分布进行溯源分析发现,入湖支流、动力船只、农田和水生植物对淀山湖总磷、氨氮和叶绿素a浓度的分布格局均有显著影响,其中入湖支流的影响最大。该研究结果可为上海市水环境立体监测提供重要参考和科学依据。

This study developed a stereoscopic network monitoring system that integrates satellite-based remote sensing,unmanned aerial vehicle(UAV)observations,and ship-based surveys to monitor the water quality of Dianshan Lake.The spatial distribution of water quality parameters was monitored and analyzed.The results demonstrated the followings:(1)The constructed water quality inversion model achieved high precision,with root mean square errors(RMSE)of 0.0191 mg/L(R^(2)=0.64,P<0.001)for total phosphorus and 0.0360 mg/L(R^(2)=0.83,P<0.001)for total nitrogen concentrations.(2)Characteristics of spatial distribution of water quality:The total phosphorus and ammonia nitrogen in Dianshan Lake are higher in the northwest and lower in the central,eastern,and western regions;the Chlorophyll-a shows a spatial distribution characterized by higher levels in the north and east,lower levels in the south and west,and higher concentrations along the shores and lower in the center.(3)Trace analysis using a generalized linear mixing model revealed significant impacts from inflowing tributaries,motorized boats,farmland,and aquatic plants on the distribution patterns of total phosphorus,ammonia nitrogen concentrations,and chlorophyll-a concentration,with inflowing tributaries having the most substantial influence.These research findings provide essential references and scientific foundations for stereoscopic network monitoring of the water environment in Shanghai.