Quantitative design and analysis of marine environmental monitoring networks in coastal waters of China

被引:14
作者
Bian, Xiaolin [1 ,2 ]
Li, Xiaoming [3 ]
Qi, Ping [4 ]
Chi, Zhenghao [3 ]
Ye, Ran [5 ]
Lu, Siwen [5 ]
Cai, Yanhong [5 ]
机构
[1] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China
[2] Deqing Acad Satellite Applicat, Lab Target Microwave Properties, Huzhou 313000, Zhejiang, Peoples R China
[3] State Ocean Adm, Beijing 100860, Peoples R China
[4] Marine Environm Monitoring Ctr Tianjin, Tianjin 300457, Peoples R China
[5] Marine Environm Monitoring Ctr Ningbo, Ningbo 315012, Zhejiang, Peoples R China
关键词
Kriging variance; Network optimization; Seawater quality; Spatial sampling; Spatial simulated annealing; ECOLOGICAL INDICATORS; OPTIMIZATION; LOCATIONS; FRAMEWORK; ESTUARY; SITES;
D O I
10.1016/j.marpolbul.2019.04.052
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
引用
收藏
页码:144 / 151
页数:8
相关论文
共 46 条
  • [1] Optimizing an estuarine water quality monitoring program through an entropy-based hierarchical spatiotemporal Bayesian framework
    Alameddine, Ibrahim
    Karmakar, Subhankar
    Qian, Song S.
    Paerl, Hans W.
    Reckhow, Kenneth H.
    [J]. WATER RESOURCES RESEARCH, 2013, 49 (10) : 6933 - 6945
  • [2] [Anonymous], 1965, Les Variables Regionalisees et Leur Estimation
  • [3] [Anonymous], 2003, Spatial Data Analysis: Theory and Practice
  • [4] [Anonymous], 1971, CAHIERS CTR MORPHOLO
  • [5] Barca E., 2014, WATER RESOUR MANAG, V29, P1
  • [6] Optimal redesign of environmental monitoring networks by using software MSANOS
    Barca, Emanuele
    Bruno, Delia E.
    Passarella, Giuseppe
    [J]. ENVIRONMENTAL EARTH SCIENCES, 2016, 75 (14)
  • [7] Water quality monitoring strategies - A review and future perspectives
    Behmel, S.
    Damour, M.
    Ludwig, R.
    Rodriguez, M. J.
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2016, 571 : 1312 - 1329
  • [8] Optimization of sample patterns for universal kriging of environmental variables
    Brus, Dick J.
    Heuvelink, Gerard B. M.
    [J]. GEODERMA, 2007, 138 (1-2) : 86 - 95
  • [9] Optimization of a hydrometric network extension using specific flow, kriging and simulated annealing
    Chebbi, Afef
    Bargaoui, Zoubeida Kebaili
    Abid, Nesrine
    Cunha, Maria da Conceicao
    [J]. JOURNAL OF HYDROLOGY, 2017, 555 : 971 - 982
  • [10] Optimization of a Coastal Environmental Monitoring Network Based on the Kriging Method: A Case Study of Quanzhou Bay, China
    Chen, Kai
    Ni, Minjie
    Cai, Minggang
    Wang, Jun
    Huang, Dongren
    Chen, Huorong
    Wang, Xiao
    Liu, Mengyang
    [J]. BIOMED RESEARCH INTERNATIONAL, 2016, 2016