Estimation of annual reference condition of Chlorophyll-a based on the segmental linear regression and power-law relationship in Taihu Lake

Abstract

Abstract 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 study's 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.