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全文摘要次数: 183 全文下载次数: 370
引用本文:

DOI:

10.11834/jrs.20219380

收稿日期:

2019-10-21

修改日期:

2021-03-19

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基于高分一号WFV影像的深圳市水库CODMn浓度时空分布特征研究
李俊1, 张文志2, 邓孺孺1, 鲁志文2, 梁业恒1, 沈雪娇2, 熊龙海1, 刘永明1
1.中山大学地理科学与规划学院,广州;2.广东省水文局惠州水文分局
摘要:

CODMn是反映水体有机污染程度的一个重要水质参数。地表水有机污染遥感监测主要面临两个挑战:技术方法大多基于经验模型,依赖大量实测数据;有机污染评价的综合性指标,水质参数不明确。针对上述问题,本文从辐射传输机理出发,基于研究区水体特征,考虑悬浮泥沙、叶绿素、耗氧性有机物三大水质因子,提出一种反演机理清晰、参数意义明确的像元反射率与CODMn浓度的物理模型。通过深圳市三大水库CODMn浓度反演与验证,决定系数R2达到0.832,模型方法可靠明。对三大水库CODMn浓度时空分布特征研究,结果表明:(1)三大水库总体CODMn浓度不高,受到轻度有机污染。(2)浓度高值区多在库角居民区附近,水库连接处未出现污染扩散。(3)2018年3月至2019年5月,库区水质改善,与2018年深圳市治水专项活动背景保持一致,建议水库水质保护核心是控制外源污染,避免丰水期污染源的输入。本文的模型方法是基于广东省典型水体光学参数,而水体固有光学特征具有季节差异,未来将进一步研究水体固光学特征变化模式,以提高模型的稳健性。此外,还可结合高分六号等谱段更多的卫星开展浅水区CODMn浓度反演的研究。

The Study of Spatial-Temporal Characteristics for CODMn in Shenzhen Reservoir Based on GF-1 WFV
Abstract:

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 needs a lot of manpower for data collection. Meanwhile, it has time and space limitations since 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, which 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 un-derstanding on mechanism is proposed in this work. 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 coefficient and scattering coefficient of oxygen-consuming organic matter, separate the contribution of the water column to the remote sensing signal from the effect of the bottom, and 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 sur-face (rrs). Experiment on the GF-1 Wide Field of View (WFV) imageries of the three major reservoirs in Shenzhen show that: the model method is reliable with overall accuracy of R2=0.832, 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 not high with average CODMn concentrations is less than 4 mg/L, and it is affect by mild organic pol-lution. No pollution diffusion occurred at the junction of the reservoirs, and the peak concentration mostly appeared near residential areas at the reservoir corner. The highest hot-spot was observed in spring and autumn, while the lowest was in Rainy summer From March 2018 to May 2019, the water quality improved, which is consistent with the back-ground of Shenzhen"s special water treatment activities in 2018. It is recommended that the core of reservoir water quality protection is to control external pollution and avoid the input of pollution sources during the flood season. In this paper, a distinct advantage of the models are broadly applicable due to their physical basis, which satisfied the requirements of the application. The model solving method is based on the inherent optical properties of typical water bodies in Guangdong Province, and inherent optical properties have seasonal variability. It is necessary to under-stand of the seasonal variations of inherent optical properties of water bodies would help to 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 resources development and policy formulation in Shenzhen, but also provide a valuable reference for the evolution of inland water organic pollution in other regions.

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