Optimization of Shanghai marine environment monitoring sites by integrating spatial correlation and stratified heterogeneity

FAN Haimei; GAO Bingbo; XU Ren; WANG Jinfeng

doi:10.1007/s13131-017-0969-3

综合空间相关性和区域分异性方法的上海海洋环境监测站位优化

doi: 10.1007/s13131-017-0969-3

1.
国家海洋局东海环境监测中心, 上海 200137
2.
北京农业信息技术研究中心, 北京 100097
3.
中国科学院地理科学与资源研究所, 资源与环境信息系统国家重点实验室, 北京 100083

基金项目: The National Natural Science Fundation of China under contract Nos 41376190, 41271404, 41531179, 41421001 and 41601425; the Open Funds of the Key Laboratory of Integrated Monitoring and Applied Technologies for Marin Harmful Algal Blooms, SOA under contract No. MATHA201120204; the Scientific Research Project of Shanghai Marine Bureau under contract No. HuHaiKe2016-05; the Ocean Public Welfare Scientific Research Project, State Oceanic Administration of the People's Republic of China under contract Nos 201305027 and 201505008.

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出版历程
- 收稿日期: 2015-10-16
- 修回日期: 2016-03-28

Optimization of Shanghai marine environment monitoring sites by integrating spatial correlation and stratified heterogeneity

1.
East China Sea Environmental Monitoring Center, State Oceanic Administration, Shanghai 201206, China
2.
Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100037, China
3.
State Key Laboratory of Resources & amp;Environmental Information System, Institute of Geographic Sciences and Nature Resources Research, Chinese Academy of Sciences, Beijing 100101, China

摘要

摘要: 综合无机氮和活性磷酸盐的海水水质类别现状进行空间分区，拟合无机氮和活性磷酸盐全局半变异函数和局部半变异函数。通过留一交叉检验方法确定统计推断方法，无机氮采用分层克里金插值方法，使得平均绝对误差和误差方差最小；活性磷酸盐采用普通克里金插值方法，使得平均绝对误差和误差方差最小。原则上调整现有站位数的10%，综合考虑对无机氮和活性磷酸盐插值标准差的变化影响，以及对不同水质类别面积的影响，确定去掉冗余的7个历史站位。7个站位均分布在劣四类水区域的长江口南支、北支、和杭州湾北部近岸区域，这些区域站点密集，水体中各要素含量变化不大，水团混合较均匀。优化删减掉的7个站位调整到三类和四类水质分区中，或者无限制区域的优化调整，发现调整优化的站位主要分布在水质类别变化过渡的区域，因此，不同水质类别的分界带以及海域边界处是站位调整优化的关键区域。
- 水质等级面积 /
- 分层克里格方法 /
- 留一法交叉检验方法 /
- 空间模拟退火方法 /
- 监测站位优化
Abstract: The water quality grades of phosphate (PO₄-P) and dissolved inorganic nitrogen (DIN) are integrated by spatial partitioning to fit the global and local semi-variograms of these nutrients. Leave-one-out cross validation is used to determine the statistical inference method. To minimize absolute average errors and error mean squares, stratified Kriging (SK) interpolation is applied to DIN and ordinary Kriging (OK) interpolation is applied to PO₄-P. Ten percent of the sites is adjusted by considering their impact on the change in deviations in DIN and PO₄-P interpolation and the resultant effect on areas with different water quality grades. Thus, seven redundant historical sites are removed. Seven historical sites are distributed in areas with water quality poorer than Grade IV at the north and south branches of the Changjiang (Yangtze River) Estuary and at the coastal region north of the Hangzhou Bay. Numerous sites are installed in these regions. The contents of various elements in the waters are not remarkably changed, and the waters are mixed well. Seven sites that have been optimized and removed are set to water with quality Grades III and IV. Optimization and adjustment of unrestricted areas show that the optimized and adjusted sites are mainly distributed in regions where the water quality grade undergoes transition. Therefore, key sites for adjustment and optimization are located at the boundaries of areas with different water quality grades and seawater.
- area of water quality grade /
- stratified Kriging (SK) /
- leave-one-out cross validation method /
- spatial simulated annealing method /
- monitoring sites optimization

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参考文献(33)

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综合空间相关性和区域分异性方法的上海海洋环境监测站位优化

doi: 10.1007/s13131-017-0969-3

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Optimization of Shanghai marine environment monitoring sites by integrating spatial correlation and stratified heterogeneity

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