Abstract：
:The quality of seawater needs to be continuously monitored due to its effect on human life and natural ecosystems. However, the balance of the extent, spatial pattern and maintenance costs of marine environmental monitoring remains a challenging issue which is crucial for decision-makers. The main contribution of this work suggests taking advantage of two minimization criteria (TMC: integrating minimization of Kriging variance and minimization of relative error at a given confidence level) to improve the design and optimization of a marine environmental monitoring network. To achieve this purpose, the spatial simulated annealing (SSA) method is applied to identify the best locations for monitoring network optimization. For the case study, phosphate (PO4) is used as an indicator to characterize the seawater quality in northern coastal waters of Zhejiang Province, China. The 122 existing sites have redundancies (about 78 sites) that can be effectively identified and removed to reduce costs with the given relative error (less than 10%) and confidence level (95%). Some new sites can be added and adjusted to improve the quality of costal environmental monitoring based on quantitative analysis. In addition, the relationship between the number of the monitoring sites and monitoring precision is analyzed. The results suggest that the present method using TMC can provide a scientific basis for marine environmental monitoring and management.
journal_name
Mar Pollut Bulljournal_title
Marine pollution bulletinauthors
Bian X,Li X,Qi P,Chi Z,Ye R,Lu S,Cai Ydoi
10.1016/j.marpolbul.2019.04.052subject
Has Abstractpub_date
2019-06-01 00:00:00pages
144-151eissn
0025-326Xissn
1879-3363pii
S0025-326X(19)30313-3journal_volume
143pub_type
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