基于对地观测信息协同的高原寒区河流水环境监测模型研究

Alpine river water environment on the Plateau (such as Tibetan Plateau) are key indicators for water security and environmental security in China. The most dominant feature for these high-altitude and closed river is the cold-arid climate condition. Due to the complex terrain and various surface eco-environment, it is a very difficult to monitor the water environment over the complex land surface of the plateau. The increasing availability of remote sensing techniques with appropriate spatiotemporal resolutions, broad coverage and low costs allows for effective monitoring river water environment on the Plateau, particularly in remote and inaccessible areas where are lack of in situ observations. In this study, we propose a remote sense-based monitoring model by using multi-platform remote sensing data for monitoring alpine river environment. Some parameterization methodologies based on satellite remote sensing data and field observations have been proposed for monitoring the water environmental parameters (including chlorophyll-a concentration (Chl-a)，total suspended solids (TSS), TN, TP, and COD, and water clarity (SD)) over the southwest highland rivers.. First, because most sensors do not collect multiple observations of a target in a single pass, data from multiple orbits or acquisition times may be used, and varying atmospheric and irradiance effects must be reconciled. So based the domestic satellite data, at first we will study the techniques of multi-sensor data correction, atmospheric correction. Second, we will build the inversion spectral database derived from long-term remote sensing data and field sampling data, and review the status of remote sensing algorithms for obtaining these water environmental parameters and testing of these algorithms. Then we will study and develop some high-precision inversion models over the southwest highland river backed by inversion spectral database through using the techniques of multi-sensor remote sensing information optimization and collaboration (optical, microwave remote sensing, et al.). Third, we will validate the key water environmental parameters and improve the inversion models. Validation of these water key parameters is crucial, both to establish the accuracy of the inversion products for the users and to provide feedback so that the data processing algorithms and inversion models can be improved. . With this project done, we hope that we would improve the monitoring and warning ability for the alpine river water environment over the southwest highland rivers, and provide information supports for the national major research project for southwest rivers in China.

西南河源区河流直接关系到我国用水安全和环境安全，对其水环境进行有效监测至关重要。但由于气候环境恶劣、下垫面复杂多样，对其水环境监测非常困难。因此，本项目拟面向西南高原高寒区河流水环境监测需求，综合应用空间对地观测技术，研究多源高分辨率遥感信息协同的水环境监测模型。利用水色遥感理论与知识过程模型，在精确测量分析水环境光谱反射特征和系统分析现有水环境参数遥感反演模型优缺点的基础上，攻克多时空多平台数据协同精准处理、精确大气校正与水环境参数高精度反演等核心技术，建立水环境各参数遥感定量反演模型，而后针对不同水环境状况结合地面观测资料优化水环境各参数遥感反演模型，最终建立精度高、适应性强的寒区河流水环境参数遥感定量监测模型，以显著提升高原高寒区河流水环境遥感监测与预警能力，也为国家重大研究计划西南河流径流变化和适应性利用提供信息支撑。

西南河源区河流直接关系到我国用水安全和环境安全，对其水环境进行有效监测至关重要。但由于气候环境恶劣、下垫面复杂多样，对其水环境监测非常困难。因此，本项目面向西南高原高寒区河流水环境监测需求，综合应用空间对地观测技术，研究了多源高分辨率遥感信息协同的水环境监测模型。通过在青藏高原高寒河流区多次野外综合观测实验，利用水色遥感理论与知识过程模型，在精确测量分析水环境光谱反射特征和系统分析现有水环境参数遥感反演模型优缺点的基础上，建立了高寒河流水环境各参数遥感定量反演模型，而后针对不同水环境状况结合地面观测资料优化水环境各参数遥感反演模型，最终建立精度高、适应性强的寒区河流水环境参数遥感定量监测模型。项目最终在国内外发表学术文章12篇，其中SCI8篇，申请专利3份，形成高寒河流水环境相关基础数据库2套。项目的相关成果能够显著提升高原高寒区河流水环境遥感监测与预警能力，也将为国家重大研究计划西南河流径流变化和适应性利用提供信息支撑。