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Open AccessArticle

Estimation of the Nutrient and Chlorophyll a Reference Conditions in Taihu Lake Based on A New Method with Extreme–Markov Theory

by Liang Wang 1, Yulin Wang 2,3,*,†, Haomiao Cheng 2 and Jilin Cheng 1,*,†
1
School of Hydraulic Energy and Power Engineering, Yangzhou University, Yangzhou 225009, China
2
School of Environmental Science and Engineering, Yangzhou University, Yangzhou 225127, China
3
Key Laboratory of Integrated Regulation and Resource Development on Shallow Lake of Ministry of Education, College of Environment, Hohai University, Nanjing 210098, China
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Int. J. Environ. Res. Public Health 2018, 15(11), 2372; https://doi.org/10.3390/ijerph15112372
Received: 9 October 2018 / Revised: 23 October 2018 / Accepted: 24 October 2018 / Published: 26 October 2018
(This article belongs to the Special Issue Water Resources Systems Quality and Quantity Management)
The nutrient reference conditions of lakes play a key role for lake water quality control and water resource management. The inferential models are important methods for calculating reference values; however, the dependence and “cluster” in time series make time series data difficult to be applied in these methods. A new method based on Markov chain theory, which is used for modeling the dependence of data, and extreme statistics was proposed. The new method was used to estimate the nutrient and chlorophyll a reference conditions in Taihu Lake, which is the third largest freshwater lake in China. The results showed that there was remarkable dependence between the effective observations of total nitrogen (TN), total phosphorus (TP), and chlorophyll a. The recommended reference conditions of TN, TP, and chlorophyll a in Taihu Lake were 0.69 mg/L, 0.029 mg/L, and 1.89 μg/L. Their 95% confidence intervals were 0.62–0.76 mg/L, 0.028–0.030 mg/L, and 1.55–2.23 μg/L. These results were consistent with previous researches, which showed that the proposed method is reliable and effective. The length of the intervals was remarkably reduced when compared with several methods. This implied that the proposed method could make full use of the observation data in time series and significantly improve the precision of the estimation results of reference conditions. In general, the proposed method could provide high precision and reliable lake nutrient reference conditions, which would be beneficial to lake water resource management and can be used for estimating the TN, TP, and chlorophyll a reference conditions of other lakes. View Full-Text
Keywords: reference condition; Markov chain; extreme method; shallow lake; high precision reference condition; Markov chain; extreme method; shallow lake; high precision
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Wang, L.; Wang, Y.; Cheng, H.; Cheng, J. Estimation of the Nutrient and Chlorophyll a Reference Conditions in Taihu Lake Based on A New Method with Extreme–Markov Theory. Int. J. Environ. Res. Public Health 2018, 15, 2372.

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