Specific inherent optical properties of highly turbid productive water for retrieval of water quality after optical classification

Assessments of specific inherent optical properties (SIOPs) and their variability in highly turbid and productive inland waters are essential for the accurate estimation of water quality. A new optical classification method including two classification criteria [i.e., normalized remote sensing refle...

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Published inEnvironmental earth sciences Vol. 73; no. 5; pp. 1961 - 1973
Main Authors Huang, Changchun, Chen, Xia, Li, Yunmei, Yang, Hao, Sun, Deyong, Li, Junsheng, Le, Chengfeng, Zhou, Liangcheng, Zhang, Mingli, Xu, Liangjiang
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer-Verlag 01.03.2015
Springer Berlin Heidelberg
Springer Nature B.V
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Summary:Assessments of specific inherent optical properties (SIOPs) and their variability in highly turbid and productive inland waters are essential for the accurate estimation of water quality. A new optical classification method including two classification criteria [i.e., normalized remote sensing reflectance slope (NS), and normalized remote sensing reflectance depth (ND)] was developed to divide remote sensing reflectance into four classes, i.e., class 1 (NS < −0.0017 and ND < 0.21) is low turbid and productive water; class 2 (NS < −0.0017 and ND > 0.21) is low turbid and high productive water; class 3 (NS > −0.0017 and ND < 0.09) is high turbid and low productive water; and class 4 (NS > −0.0017 and ND > 0.009) is high turbid and high productive water. The relationships between phytoplankton absorption at 440 nm [aₚₕ(440)] and chlorophyll-a concentration [Ccₕₗₐ] as well as between particle backscattering coefficient at 440 nm [bbₚ(440)] and total suspended matter concentration (CTSM) after classification were obtained from a large number of in situ data in Lake Taihu. The measured specific phytoplankton absorption [Formula: see text] and particle backscattering coefficient [Formula: see text] show significant variations even within the same class. The mean values of [Formula: see text] at 440 nm [Formula: see text] for each class are 0.048 ± 0.013, 0.060 ± 0.012, 0.083 ± 0.021, and 0.056 ± 0.017 m²/mg, respectively. The mean values of [Formula: see text] at 440 nm [Formula: see text] for each class are 0.035 ± 0.01, 0.024 ± 0.004, 0.041 ± 0.009, and 0.038 ± 0.009 m²/g, respectively. The power functions of SIOPs and water constituents’ concentration indicate that [Formula: see text] and [Formula: see text] vary with Ccₕₗₐand CTSM. The validation results show that our proposed values for [Formula: see text] and [Formula: see text] cover a very wide range of water optical properties, which are characterized from clear water to highly turbid productive water. The validation results also suggest that the retrieval accuracy of Ccₕₗₐand CTSMbio-optical model was improved after classification. The root mean square error (RMSE) of Ccₕₗₐwas improved from 14.18 to 7.43 μg/L (mean value of all classes) and RMSE of CTSMwas improved from 32.98 to 26.10 mg/L (mean value of all classes). Thus, the temporal and spatial variation of [Formula: see text] and [Formula: see text] should be considered in the bio-optical retrieval model of water quality.
Bibliography:http://dx.doi.org/10.1007/s12665-014-3548-3
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ISSN:1866-6280
1866-6299
DOI:10.1007/s12665-014-3548-3