Optimization of a Coastal Environmental Monitoring Network Based on the Kriging Method: A Case Study of Quanzhou Bay, China

• Published in: BioMed research international 2016-01, Vol.2016 (2016), p.1-12
• Main Authors: Liu, Mengyang, Chen, Huorong, Huang, Dongren, Wang, Jun, Cai, Minggang, Ni, Minjie, Chen, Kai, Wang, Xiao
• Format: Article
• Language: English
• Subjects: Algorithms; Analysis; Bays; Biological Oxygen Demand Analysis; Case studies; China; Coastal zone management; Coasts; Design optimization; Discount department stores; Discriminant analysis; Ecosystem; Environmental monitoring; Environmental Monitoring - methods; Environmental quality; Geography; Inorganic Chemicals - analysis; Laboratories; Methods; Network management systems; Nitrogen - analysis; Phosphates - analysis; Pollution; Principal components analysis; Quality; Reference Standards; River ecology; Science; Seawater - chemistry; Statistical analysis; Time series
• ISSN: 2314-6133; 2314-6141
• DOI: 10.1155/2016/7137310

Environmental monitoring is fundamental in assessing environmental quality and to fulfill protection and management measures with permit conditions. However, coastal environmental monitoring work faces many problems and challenges, including the fact that monitoring information cannot be linked up with evaluation, monitoring data cannot well reflect the current coastal environmental condition, and monitoring activities are limited by cost constraints. For these reasons, protection and management measures cannot be developed and implemented well by policy makers who intend to solve this issue. In this paper, Quanzhou Bay in southeastern China was selected as a case study; and the Kriging method and a geographic information system were employed to evaluate and optimize the existing monitoring network in a semienclosed bay. This study used coastal environmental monitoring data from 15 sites (including COD, DIN, and PO4-P) to adequately analyze the water quality from 2009 to 2012 by applying the Trophic State Index. The monitoring network in Quanzhou Bay was evaluated and optimized, with the number of sites increased from 15 to 24, and the monitoring precision improved by 32.9%. The results demonstrated that the proposed advanced monitoring network optimization was appropriate for environmental monitoring in Quanzhou Bay. It might provide technical support for coastal management and pollutant reduction in similar areas.