Changes of water clarity in large lakes and reservoirs across China observed from long-term MODIS

REMOTE SENSING OF ENVIRONMENT

卷:247

Article

Wang, Shenglei^1,2  Li, Junsheng^2,3  Zhang, Bing^2,3  Lee, Zhongping⁴  Spyrakos, Evangelos⁵  Feng, Lian⁶  Liu, Chong⁷  Zhao, Hongli⁸  Wu, Yanhong²  Zhu, Liping⁷  Jia, Liming⁹  Wan, Wei¹  Zhang, Fangfang²  Shen, Qian²  Tyler, Andrew N.⁵  Zhang, Xianfeng¹ 

[1] Peking Univ, Sch Earth & Space Sci, Beijing, Peoples R China

[2] Chinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, 9 Dengzhuang South Rd Haidian Dist, Beijing 100094, Peoples R China

[3] Univ Chinese Acad Sci, Beijing, Peoples R China

[4] Univ Massachusetts, Sch Environm, Boston, MA 02125 USA

[5] Univ Stirling, Fac Nat Sci Biol & Environm Sci, Stirling, Scotland

[6] Southern Univ Sci & Technol, Sch Environm Sci & Engn, State Environm Protect Key Lab Integrated Surface, Shenzhen, Peoples R China

[7] Chinese Acad Sci, Inst Tibetan Plateau Res, Key Lab Tibetan Environm Changes & Land Surface P, Beijing, Peoples R China

[8] China Inst Water Resources & Hydropower Res, Beijing, Peoples R China

[9] Environm Monitoring Cent Stn Heilongjiang Prov, Harbin, Peoples R China

关键词: Secchi disk depth;    Lakes and reservoirs;    MODIS;    FUI;    Hue angle;    Water clarity changes;   

DOI  :  10.1016/j.rse.2020.111949

来源: Elsevier

【 摘 要 】

Water clarity is a well-established first-order indicator of water quality and has been used globally by water regulators in their monitoring and management programs. Assessments of water clarity in lakes over large temporal and spatial scales, however, are rare, limiting our understanding of its variability and the driven forces. In this study, we developed and validated a robust Secchi disk depth (Z(SD)) algorithm for lakes across China based on two water color parameters, namely Forel-Ule Index (FUI) and hue angle alpha, retrieved from MODIS data. The MODIS Z(SD) model shows good results when compared with in-situ measurements from 17 lakes, with a 27.4% mean relative difference (MRD) in the validation dataset. Compared with other empirical Z(SD) models, our FUI and alpha-based model demonstrates improved performance and adaptability over a wide range of water clarity and trophic states. This algorithm was subsequently applied to MODIS measurements to provide a comprehensive assessment of water clarity in large lakes (N = 153) across China for the first time. The mean summer Z(SD) of the studied lakes between 2000 and 2017 demonstrated marked spatial and temporal variations. Spatially, the Z(SD) of large lakes presented a distinct spatial pattern of high west and low east over China. This spatial pattern was found to be associated with the significant differences in lake depth and altitude between west and east China while China's population, GDP, temperature, and precipitation distribution have also contributed to a certain extent. Temporally, the Z(SD) of most lakes increased during this period, with an overall mean rate of 3.3 cm/yr for all lakes. Here, 38.6% (N = 59) of the lakes experienced a significant increase in their Z(SD) value during the past 18 years while only 8.5% (N = 13) showed a significant decreasing trend. Significant increases in lake Z(SD) were observed in west China, which were found to correlate with the increase of air temperature and lake surface area. This is possibly a response of the lakes in west China to climate change. In the lake systems of east China, which are predominately used as a drinking water source, the increase in lake Z(SD) was found to be strongly correlated with changes in local GDP (gross domestic production), NDVI (normalized difference vegetation index) and lake surface area, suggesting a combined effect of the implemented management practices and climatic variability. The results of this study provide important information for water quality conservation and management in China, and also highlight the value of satellite remote sensing in monitoring water quality over lakes at a large scale and long-term.

【 授权许可】

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