MODIS observations of cyanobacterial risks in a eutrophic lake: Implications for long-term safety evaluation in drinking-water source

WATER RESEARCH

卷:122

Article

Duan, Hongtao¹  Tao, Min¹  Loiselle, Steven Arthur²  Zhao, Wei³  Cao, Zhigang¹  Ma, Ronghua¹  Tang, Xiaoxian⁴ 

[1] Chinese Acad Sci, Nanjing Inst Geog & Limnol, Key Lab Watershed Geog Sci, Nanjing 210008, Jiangsu, Peoples R China

[2] Univ Siena, CSGI, Dipartimento Farmaco Chim Tecnol, I-53100 Siena, Italy

[3] Minist Environm Protect, Nanjing Inst Environm Sci, Nanjing 210042, Jiangsu, Peoples R China

[4] Chaohu Lake Management Author, Monitoring Stn, Chaohu 238000, Peoples R China

关键词: Remote sensing;    PC;    Algal bloom;    Lake Chaohu;    Cyanobacterial dominance;   

DOI  :  10.1016/j.watres.2017.06.022

来源: Elsevier

【 摘 要 】

The occurrence and related risks from cyanobacterial blooms have increased world-wide over the past 40 years. Information on the abundance and distribution of cyanobacteria is fundamental to support risk assessment and management activities. In the present study, an approach based on Empirical Orthogonal Function (EOF) analysis was used to estimate the concentrations of chlorophyll a (Chla) and the cyanobacterial biomarker pigment phycocyanin (PC) using data from the MODerate resolution Imaging Spectroradiometer (MODIS) in Lake Chaohu (China's fifth largest freshwater lake). The approach was developed and tested using fourteen years (2000-2014) of MODIS images, which showed significant spatial and temporal variability of the PC:Chla ratio, an indicator of cyanobacterial dominance. The results had unbiased RMS uncertainties of <60% for Chla ranging between 10 and 300 mu g/L, and unbiased RMS uncertainties of <65% for PC between 10 and 500 mu g/L. Further analysis showed the importance of nutrient and climate conditions for this dominance. Low TN:TP ratios (<29:1) and elevated temperatures were found to influence the seasonal shift of phytoplankton community. The resultant MODIS Chla and PC products were then used for cyanobacterial risk mapping with a decision tree classification model. The resulting Water Quality Decision Matrix (WQDM) was designed to assist authorities in the identification of possible intake areas, as well as specific months when higher frequency monitoring and more intense water treatment would be required if the location of the present intake area remained the same. Remote sensing cyanobacterial risk mapping provides a new tool for reservoir and lake management programs. (C) 2017 Elsevier Ltd. All rights reserved.

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