Estimation of annual reference condition of Chlorophyll-a based on the segmental linear regression and power-law relationship in Taihu Lake
Author(s) -
Liang Wang,
Zulin Hua,
Yulin Wang
Publication year - 2018
Publication title -
water science and technology water supply
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.318
H-Index - 39
eISSN - 1607-0798
pISSN - 1606-9749
DOI - 10.2166/ws.2018.060
Subject(s) - linear regression , chlorophyll , chlorophyll a , environmental science , regression analysis , regression , statistics , mathematics , quantile , biology , botany
The reference conditions of Chlorophyll- a in lakes should be established in order to improve the water quality in these water bodies. A new method using segmental linear regression was developed to estimate the reference condition of Chlorophyll- a . The method can overcome the shortcomings of other methods, such as the quantile-selection-based method, which contains a certain level of subjectivity. The new method was used to estimate the annual reference condition of Chlorophyll- a in Taihu Lake. The log–log segmental regression results indicate that the distribution of specific volume (reciprocal of concentration) of Chlorophyll- a in Taihu Lake had a power-law tail. Both segmental regression and bootstrap approaches show two credible change points in the power-law relationship. This study9s analysis shows that the value of 4.4 mg·m −3 was an appropriate annual reference value of Chlorophyll- a in Taihu Lake. Thus, the method would be useful in determining the numerical reference conditions of Chlorophyll- a for other shallow lakes.
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