Literature DB >> 29096974

Semivariance analysis and transinformation entropy for optimal redesigning of nutrients monitoring network in San Francisco bay.

Amir Boroumand1, Taher Rajaee2, Fariborz Masoumi3.   

Abstract

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.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Nutrients; Optimum distance; San Francisco Bay; Semivariance; Transinformation entropy; Water quality monitoring networks

Mesh:

Substances:

Year:  2017        PMID: 29096974     DOI: 10.1016/j.marpolbul.2017.10.057

Source DB:  PubMed          Journal:  Mar Pollut Bull        ISSN: 0025-326X            Impact factor:   5.553


  2 in total

1.  Soil moisture assessment through the SSMMI and GSSIM algorithm based on SPOT, WorldView-2, and Sentinel-2 images in the Daliuta Coal Mining Area, China.

Authors:  Hui Yue; Ying Liu; Jiaxin Qian
Journal:  Environ Monit Assess       Date:  2020-03-15       Impact factor: 2.513

2.  Assessment of natural groundwater reserve of a morphodynamic system using an information-based model in a part of Ganga basin, Northern India.

Authors:  N C Mondal; V Ajaykumar
Journal:  Sci Rep       Date:  2022-04-13       Impact factor: 4.379

  2 in total

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