Civil Engineering Dept., Faculty of Engineering, University of Qom, Qom, Iran.
Civil Engineering Dept., Faculty of Engineering, University of Qom, Qom, Iran.
Mar Pollut Bull. 2018 Apr;129(2):689-694. doi: 10.1016/j.marpolbul.2017.10.057. Epub 2017 Oct 31.
This paper introduces a Semivariance-Transinformation (S-T) based method for designing an optimum bay water nutrients monitoring network in San Francisco bay (S.F. bay), USA. Phosphorus and nitrogen are the most important nutrients that lead to eutrophic condition. The monthly phosphate and nitrate+nitrite data recorded during September 2006 to August 2015 was obtained over 14 active stations located at S.F. bay and was used in the research. Semivariance and discrete transinformation entropy have been applied to calculate the optimum range of the monitoring distance. The study indicated the ranges of 28 to 82 and 37 to 50km for the phosphate and nitrate+nitrite respectively. Useful information can be obtained from the monitoring network, if the monitoring distance is included in the mentioned intervals. The findings of the research introduce a new approach in the field of water quality monitoring networks design.
本文介绍了一种基于半方差-信息传输量（S-T）的方法，用于设计美国旧金山湾（S.F.湾）的最佳湾水营养物监测网络。磷和氮是导致富营养化的最重要的营养物质。本研究使用了 2006 年 9 月至 2015 年 8 月期间在旧金山湾 14 个活跃站点记录的每月磷酸盐和硝酸盐+亚硝酸盐数据。半方差和离散信息传输熵已被应用于计算最佳监测距离范围。研究表明，磷酸盐和硝酸盐+亚硝酸盐的最佳监测距离范围分别为 28 至 82km 和 37 至 50km。如果监测距离包含在所述区间内，则可以从监测网络中获得有用信息。该研究的结果为水质监测网络设计领域引入了一种新方法。
