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Study of spatial—temporal characteristics for CODMn in Shenzhen reservoir based on GF-1 WFV

  • role： First author第一作者
  • Affiliation：

    School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China

    Guangdong Engineering Research Center of Water Environment Remote Sensing Monitoring, Guangzhou 510275, China

    Guangdong Provincial Key Laboratory of Urbanization and Geo-Simulation, Guangzhou 510275, China

  • Email：lijun259@mail3.sysu.edu.cn
  • Introduction：李俊，研究方向为水质定量遥感。E-mail： lijun259@mail3.sysu.edu.cn
LI Jun123,  
  • Affiliation：

    Huizhou branch of Guangdong Hydrology Bureau, Huizhou 516003,China

ZHANG Wenzhi4,  
  • role： Corresponding author通信作者
  • Affiliation：

    School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China

    Guangdong Engineering Research Center of Water Environment Remote Sensing Monitoring, Guangzhou 510275, China

    Guangdong Provincial Key Laboratory of Urbanization and Geo-Simulation, Guangzhou 510275, China

  • Email：eesdrr@mail.sysu.edu.cn
  • Introduction：邓孺孺，研究方向为水质遥感与大气环境遥感。E-mail： eesdrr@mail.sysu.edu.cn
DENG Ruru123*,  
  • Affiliation：

    Huizhou branch of Guangdong Hydrology Bureau, Huizhou 516003,China

LU Zhiwen4,  
  • Affiliation：

    School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China

LIANG Yeheng1,  
  • Affiliation：

    Huizhou branch of Guangdong Hydrology Bureau, Huizhou 516003,China

SHEN Xuejiao4,  
  • Affiliation：

    School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China

XIONG Longhai1,  
  • Affiliation：

    School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China

LIU Yongming1

resumen

Permanganate index (CODMn) is an important water quality parameter to reflect the degree of organic pollution. At present, the retrieval of organic pollution by remote sensing technology is mostly based on empirical models and requires considerable manpower for data collection. Meanwhile, it has time and space limitations because it cannot process each image under different imaging conditions adaptively. The integrated water quality index, CDOM, and DOC of the inverted parameters are not water quality indexes. Thus, they cannot be directly used for actual water quality evaluation. Therefore, a novel quantitative remote sensing technology method for the retrieval of water permanganate index with clear understanding on mechanism is proposed.The method based on the radiation transmission process of electromagnetic waves and the characteristics of the water body in the study area consider the three major water quality factors of suspended sediment, chlorophyll, and oxygen-consuming organic, analyze the absorption and scattering coefficients of oxygen-consuming organic matter, and separate the contribution of the water column to the remote sensing signal from the effect of the bottom. The diffuse extinction coefficients (c) of water quality components are expressed as functions of in-water absorption (a) and scattering (b). Finally, the concentration of CODMn was derived with the remote-sensing reflectance below the surface (rrs).The experiment on the GF-1 Wide Field of View (WFV) imageries of the three major reservoirs in Shenzhen shows that the model method is reliable with overall accuracy of R2=0.832 and RMSE=46.4%. The spatial—temporal characteristics of the three major reservoirs in Shenzhen during 2018—2019 were investigated. The overall CODMn concentration of the three major reservoirs is low with average CODMn concentrations of less than 4 mg/L; it is affected by mild organic pollution. No pollution diffusion occurred at the junction of the reservoirs, and the peak concentration mostly appeared near the residential areas at the reservoir corner. The highest hotspot was observed in spring and autumn, whereas the lowest was in rainy summer From March 2018 to May 2019. The water quality improved, consistent with the background of Shenzhen’s special water treatment activities in 2018. The core of reservoir water quality protection is recommended to control external pollution and avoid the input of pollution sources during the flood season.A distinct advantage of the models is broadly applicable due to their physical basis, which satisfied the application requirements. The model solving method is based on the inherent optical properties of typical water bodies in Guangdong Province, and these properties have seasonal variability. The seasonal variations of inherent optical properties of water bodies can improve the stability of the model. In addition, the spectrum of shallow waters is affected by the depth and the reflection at the bottom. CODMn concentration inversion from satellite data with more spectrum bands remains underexplored. The RS scheme used in this study can not only provide support for inland water resource development and policy formulation in Shenzhen, but also a valuable reference for the evolution of inland water organic pollution in other regions.

palabra clave

permanganate index;Organic pollution;absorption coefficient;GF-1 WFV;Shenzhen;water quality remote sensing

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