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Water Bloom Precursor Analysis Based on Two Direction S-Rough Set

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Abstract

In the field of water quality management, it is vital to determine the main precursory anomalies from the precursor of intricate water bloom in the context of a given area. In this paper, a water bloom precursor analysis method, based on two direction singular rough set, was proposed. This approach was produced on the basis of the different sections and pre-water bloom of water bloom precursor anomalies and characteristic of elements transferred in singular rough set. For testing the validity of two direction singular rough set application in water bloom precursor analysis, Xiangxi River, which is one of the typical tributaries of Three Gorges Reservoir in China, was selected as study area. The result showed that compared with other indexes, pH and dissolved oxygen (DO) are the most valuable indicators of water bloom in the precursory anomalies. Furthermore, regarding with water bloom precursory anomalies in Xiangxi River, most of the nutrient loading and biological community are the key indicators. Hence, this method can determine the main precursory anomaly for water bloom in the study area, which provides powerful knowledge support to water quality specialists for them to comprehensively analyze precursory anomaly so as to find out its relationship with occurrence law of water bloom.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 61602434), the Chongqing Research Program of Basic Research and Frontier Technology under Grant cstc2015jcyjB0244, the Application Development Plan Project of Chongqing (cstc2014yykfC0053), the National Natural Science Foundation of China (No.51609229), the Key Natural Science Foundation of Chongqing (No.CSTC2013jjB40003), and the support of the National Science and Technology Major Project of China (2014ZX07104-006). The authors would like to thank the editor and anonymous referees for their useful comments and valuable suggestions to improve the composition and content substantially.

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Authors and Affiliations

  1. Big Data Mining and Applications Center, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, 400714, China

    Huyong Yan, Guoyin Wang, Di Wu, Yu Huang, Mingsheng Shang, Jianjun Xu, Kun Shan, Xiaoyu Shi, Jianhua Dong, Lei Feng, Botian Zhou & Ye Yuan

  2. University of Chinese Academy of Sciences, Beijing, 100049, China

    Huyong Yan, Di Wu & Jianhua Dong

  3. Yubei Municipal Gardens Bureau, Chongqing, 401120, China

    Yufei Zhao

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  1. Huyong Yan
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  2. Guoyin Wang
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  4. Yu Huang
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Correspondence to Huyong Yan.

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Guoyin Wang, Di Wu and Yu Huang contributed equally to this work.

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Yan, H., Wang, G., Wu, D. et al. Water Bloom Precursor Analysis Based on Two Direction S-Rough Set. Water Resour Manage 31, 1435–1456 (2017). https://doi.org/10.1007/s11269-017-1579-8

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  • DOI: https://doi.org/10.1007/s11269-017-1579-8

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