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The proposal， practice and preliminary application of land-based （ground-based， shore-based） remote sensing of water environment

  • role： First author第一作者
  • Affiliation：

    State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China

  • Email：ylzhang@niglas.ac.cn
  • Introduction：张运林，1976年生，男，研究员，研究方向为物理湖泊学、水色遥感以及有色可溶性有机物循环。E-mail： ylzhang@niglas.ac.cn
ZHANG Yunlin1,  
  • Affiliation：

    State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China

SHI Kun1,  
  • Affiliation：

    State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China

ZHANG Yibo1,  
  • Affiliation：

    State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China

SUN Xiao1,  
  • Affiliation：

    State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China

LI Na1,  
  • Affiliation：

    State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China

HUANG Xin1,  
  • Affiliation：

    State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China

WANG Weijia1,  
  • Affiliation：

    State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China

ZHOU Yongqiang1,  
  • Affiliation：

    Hangzhou Hikvision Digital Technology Co., Ltd, Hangzhou 310051, China

GAO Yanghui2,  
  • Affiliation：

    Hangzhou Hikvision Digital Technology Co., Ltd, Hangzhou 310051, China

CAI Hong2,  
  • Affiliation：

    Hangzhou Hikvision Digital Technology Co., Ltd, Hangzhou 310051, China

GAO Jing2

Resümee

Cross-section monitoring is an important cornerstone to accurately grasp the surface water quality and water environment change characteristics, to explore water environment formation mechanism, to evaluate and assess water environment trend, to treat and repair water pollution, and to manage water quality. Improving the level of three-dimensional, automatic and intelligent monitoring is an important direction of future ecological environment monitoring, which can effectively improve the level of modern ecological environment monitoring ability.The traditional cross-section manual sampling monitoring is time-consuming and laborious, and the time and space frequency are very low resulting in the discrete data and the poor timeliness. High frequency on-line monitoring of underwater sensors can solve the continuous observation in time, but the sensor is easy to wear and tear and disturbed by water environment, resulting in unstable monitoring accuracy, limited monitoring indexes, large errors between automatic monitoring results of key parameters such as total nitrogen and total phosphorus and conventional laboratory monitoring analysis data. In addition, high management and maintenance costs are needed for the on-line monitoring of underwater sensors. Satellite remote sensing can realize the inversion of key water quality parameters in different spatial scales, but it is difficult to solve the high temporal resolution continuous observation. Meanwhile, it is difficult to ensure high-precision monitoring due to the effects of cloud and rain conditions and atmospheric correction.In this study, we firstly propose the concept of land-based (ground-based, shore-based) water environment remote sensing to effectively supplement and improve the existing satellite remote sensing and national surface water environment cross-section monitoring technology and methods. Using domestic hyperspectral imager developed by the Hangzhou Hikvision Digital Technology Co., Ltd. and Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, we carry out the application practice of land-based (ground-based, shore-based) water environment remote sensing under complex weather and water conditions in Lake Taihu. Based on the in situ measurement of remote sensing reflectance and key water quality parameters, we calibrate and validate the remote sensing estimation models of Secchi disc depth, total suspended matter, total nitrogen, and total phosphorus with high precision. Overall, the estimation precisions of four key water quality parameters are close or higher than 80% indicating the land-based (ground-based, shore-based) remote sensing can be used for the accurate monitoring of water quality under complex weather and water conditions. High frequency dynamic processes of key water quality parameters are observed by implanting remote sensing estimation models into the hyperspectral imager, which can be used to finely characterize time evolution process of water environment. The practice of remote sensing of water environment in Lake Taihu shows that it has a wide application prospect and market value to install domestic hyperspectral imager to carry out high frequency accurate observation of key water quality parameters in the national surface water monitoring section.Of course, more in situ observation and measurement for different waters are needed to improve or develop universal models for more parameters monitoring. Coupled with satellite, unmanned aerial vehicle and land-based (ground-based, shore based) remote sensing, the sky-air-ground integrated remote sensing monitoring system can be established. Combined with cross-section manual monitoring and automatic observation, the collaborative monitoring can be carried out to give full play to their respective advantages, which truly realize the long-term reconstruction and real-time high-frequency dynamic monitoring of key water quality parameters serving water environment management.

Schlüsselwort

land-based (ground-based, shore-based) remote sensing;water quality parameters;total suspended matter;nutrients;total phosphorus;secchi disc depth

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