The study on optimal design of river monitoring network using modified approaching degree model: a case study of the Lia
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RESEARCH ARTICLE
The study on optimal design of river monitoring network using modified approaching degree model: a case study of the Liaohe River, Northeast China Hui Wang 1 & Zhenheng Jiao 1 & Liusuo Wang 2 & Yinggang Wang 1 & Qing Luo 1 & Hao Wu 1 & Xiaoxu Wang 1 & Lina Sun 1 Received: 25 April 2020 / Accepted: 16 July 2020 # Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract This paper proposes a quantitative method to optimize the existing river monitoring network based on a modified approaching degree model, T test, and Euclidean distance. In this study, the Liaohe River located in Liaoning province, China, was taken as a research object. Samples were collected from 8 sampling sites throughout the monitoring network, and water quality parameters were analyzed every 2 months from January 2009 to December 2010. The results show that the average concentrations of the ammonia nitrogen (NH4+-N) and chemical oxygen demand (COD) were beyond grade III of the Environmental Quality Standards for Surface Water of China (GB3838-2002), and they were the main water quality parameters. After optimization, the number of monitoring sections along the Liaohe River was reduced to five from the original eight, thus saving 37.5% of the monitoring cost; meanwhile, there is no significant difference between the un-optimized and optimized monitoring networks, and the optimized monitoring network remains to be able to perform as good as the original one. In addition, the total data attainment rate was improved greatly, and the duplicate setting degree of monitoring points decreased significantly compared with other optimal methods. The optimized monitoring network proves to be more efficient, reasonable, and economically feasible, so this quantitative method can help optimize the changing orderly river monitoring networks. Keywords Liaohe River . Approaching degree model . Optimal design . River monitoring network
Introduction Rivers are an essential source of fresh water for socioeconomic development, and the quality of river water is becoming a very sensitive topic (Mishra 2010). On the other
hand, pollutants are being discharged into rivers in different ways, causing severe effects on the water environment and people’s lives (Memet 2013; Ahmed et al. 2015). In order to protect our water environment, we must get accurate water quality data. The water quality monitoring has begun since
Responsible Editor: Marcus Schulz * Yinggang Wang [email protected]
Xiaoxu Wang [email protected]
Hui Wang [email protected]
Lina Sun [email protected]
Zhenheng Jiao [email protected] 1
Key Laboratory of the Ministry of Education for Regional Environmental and Eco-Remediation, Shenyang University, Shenyang 110044, People’s Republic of China
2
Liaoning Provincial Scientific and Technical Center for Ecological Environment Protection, Shenyang 110000, People’s Republic of China
Liusuo Wang [email protected] Qing Luo [email protected] Hao Wu [email protected]
Environ Sci Pollut Res
the 1960s so as to better protect water resour
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