断面监测是准确掌握中国地表水水质和水环境变化特征，开展水环境成因机制分析、评价评估、治理修复和管理考核的重要基石。提高监测立体化、自动化、智能化水平是未来水生态环境监测的重要方向，可以切实提高中国生态环境监测现代化能力。本文针对全国地表水环境断面监测，首次提出陆基（地基、岸基）水环境遥感概念，有效补充和完善传统的卫星遥感和断面监测技术方法。通过与杭州海康威视数字技术股份有限公司（简称“海康威视”）开展合作研发，自主研制了国产高光谱成像仪，于2020-07-31—2020-08-17在太湖开展了复杂天况和水况场景下陆基（地基、岸基）水环境遥感实践应用，构建了透明度、悬浮物、总氮、总磷等关键水质参数高精度遥感反演算法，反演精度可达80%及以上。将相关算法植入高光谱成像仪中获得关键水质参数高频动态变化过程，精细刻画其时间演化过程。太湖陆基（地基、岸基）水环境遥感实践表明，在全国地表水监测断面架设国产高光谱成像仪开展关键水质参数高频精准观测具有广泛应用前景和市场推广价值，可以与卫星和无人机遥感形成天—空—地立体化遥感监测体系，结合断面人工巡测和自动观测开展协同监测。

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.