| 摘要: |
| 淀山湖是上海最大的淡水湖和重要水源地。为了保护和监测淀山湖的水环境,通过卫星、无人机遥感和走航船实时监测建立淀山湖天空地一体化立体水质监测网络,并对淀山湖水质参数的空间分布格局进行了溯源分析。结果表明:(1)天空地一体立体水质监测网络对淀山湖的水源安全监测具有重要作用；(2)建立了淀山湖天地水质参数反演模型,水质反演结果与走航实测水质浓度结果验证可用。其中总磷浓度反演结果的均方根误差为0.0206 mg/L(R2=0.64, P<0.001)；总氮浓度反演结果的均方根误差为0.2731 mg/L(R2=0.83, P<0.001)。(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、氨氮浓度和对叶绿素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。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。 |
| 关键词: 立体监测网络 淀山湖 水质监测 溯源分析 |
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| The remote sensing monitoring and tracing analysis of water quality in the integrated space-air-ground integrated network, a case study in Dianshan Lake |
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| Abstract: |
| Dianshan Lake is the largest freshwater lake and an essential water source in Shanghai. To protect and monitor its water environment, a three-dimensional water quality monitoring network has been established through satellite, drone remote sensing, and real-time monitoring on cruising boats. Additionally, a traceability analysis has been conducted to investigate the spatial distribution patterns of water quality parameters in Dianshan Lake. The results indicate that: (1) The three-dimensional water quality monitoring network plays a crucial role in monitoring the water safety of Dianshan Lake; (2) A water quality parameter inversion model for Dianshan Lake has been established, and the inversion results have been verified to be reliable through comparisons with the measured water quality concentrations from cruising boats. Specifically, the root mean square error of the total phosphorus concentration inversion result is 0.0206 mg/L (R2=0.64, P<0.001), while the root mean square error of the total nitrogen concentration inversion result is 0.2731 mg/L (R2=0.83, P<0.001); (3) A generalized linear mixed model was employed to conduct a traceability analysis of the spatial distribution of water quality in Dianshan Lake. It was found that inflow tributaries, motorized boats, farmland, and aquatic plants have significant impacts on the distribution patterns of total phosphorus, ammonia nitrogen, and chlorophyll-a concentrations in Dianshan Lake, with the inflow tributaries exerting the most significant influence. These findings provide important references and scientific basis for the three-dimensional monitoring of the water environment in Shanghai. |
| Key words: Three-dimensional monitoring network Dianshan Lake water quality monitoring source tracing analysis |
