IDEAS home Printed from https://ideas.repec.org/a/gam/jdataj/v3y2018i4p50-d181172.html
   My bibliography  Save this article

Application of Rough Set Theory to Water Quality Analysis: A Case Study

Author

Listed:
  • Maryam Zavareh

    (Department of Civil, Environmental and Infrastructure Engineering, George Mason University, Fairfax, VA 22030, USA)

  • Viviana Maggioni

    (Department of Civil, Environmental and Infrastructure Engineering, George Mason University, Fairfax, VA 22030, USA)

Abstract

This work proposes an approach to analyze water quality data that is based on rough set theory. Six major water quality indicators (temperature, pH, dissolved oxygen, turbidity, specific conductivity, and nitrate concentration) were collected at the outlet of the watershed that contains the George Mason University campus in Fairfax, VA during three years (October 2015–December 2017). Rough set theory is applied to monthly averages of the collected data to estimate one indicator (decision attribute) based on the remainder indicators and to determine what indicators (conditional attributes) are essential (core) to predict the missing indicator. The redundant attributes are identified, the importance degree of each attribute is quantified, and the certainty and coverage of any detected rule(s) is evaluated. Possible decision making rules are also assessed and the certainty coverage factor is calculated. Results show that the core water quality indicators for the Mason watershed during the study period are turbidity and specific conductivity. Particularly, if pH is chosen as a decision attribute, the importance degree of turbidity is higher than the one of conductivity. If the decision attribute is turbidity, the only indispensable attribute is specific conductivity and if specific conductivity is the decision attribute, the indispensable attribute beside turbidity is temperature.

Suggested Citation

  • Maryam Zavareh & Viviana Maggioni, 2018. "Application of Rough Set Theory to Water Quality Analysis: A Case Study," Data, MDPI, vol. 3(4), pages 1-15, November.
    • Handle: RePEc:gam:jdataj:v:3:y:2018:i:4:p:50-:d:181172
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2306-5729/3/4/50/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2306-5729/3/4/50/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Maria Diamantopoulou & Vassilis Antonopoulos & Dimitris Papamichail, 2007. "Cascade Correlation Artificial Neural Networks for Estimating Missing Monthly Values of Water Quality Parameters in Rivers," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(3), pages 649-662, March.
    2. Si-Hui Dong & Hui-Cheng Zhou & Hai-Jun Xu, 2004. "A Forecast Model of Hydrologic Single Element Medium and Long-Period Based on Rough Set Theory," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 18(5), pages 483-495, October.
    3. Ajit Singh & S. Ghosh & Pankaj Sharma, 2007. "Water quality management of a stretch of river Yamuna: An interactive fuzzy multi-objective approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(2), pages 515-532, February.
    4. Ping-Feng Pai & Fong-Chuan Lee, 2010. "A Rough Set Based Model in Water Quality Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(11), pages 2405-2418, September.
    5. Ping-Feng Pai & Lan-Lin Li & Wei-Zhan Hung & Kuo-Ping Lin, 2014. "Using ADABOOST and Rough Set Theory for Predicting Debris Flow Disaster," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(4), pages 1143-1155, March.
    6. X. Qin & G. Huang, 2009. "An Inexact Chance-constrained Quadratic Programming Model for Stream Water Quality Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(4), pages 661-695, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ping-Feng Pai & Fong-Chuan Lee, 2010. "A Rough Set Based Model in Water Quality Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(11), pages 2405-2418, September.
    2. Huapeng Qin & Jingjing Jiang & Guangtao Fu & Ying Zheng, 2013. "Optimal Water Quality Management Considering Spatial and Temporal Variations in a Tidal River," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(3), pages 843-858, February.
    3. Huyong Yan & Guoyin Wang & Di Wu & Yu Huang & Mingsheng Shang & Jianjun Xu & Kun Shan & Xiaoyu Shi & Jianhua Dong & Lei Feng & Botian Zhou & Ye Yuan & Yufei Zhao, 2017. "Water Bloom Precursor Analysis Based on Two Direction S-Rough Set," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(5), pages 1435-1456, March.
    4. M. Islam & Rehan Sadiq & Manuel Rodriguez & Homayoun Najjaran & Alex Francisque & Mina Hoorfar, 2013. "Evaluating Water Quality Failure Potential in Water Distribution Systems: A Fuzzy-TOPSIS-OWA-based Methodology," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(7), pages 2195-2216, May.
    5. Yonas Ghile & Roland Schulze, 2010. "Evaluation of Three Numerical Weather Prediction Models for Short and Medium Range Agrohydrological Applications," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(5), pages 1005-1028, March.
    6. Huaizhi Su & Meng Yang & Yeyuan Kang, 2016. "Comprehensive Evaluation Model of Debris Flow Risk in Hydropower Projects," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(3), pages 1151-1163, February.
    7. Bojan Srdjevic & Yvonilde Medeiros, 2008. "Fuzzy AHP Assessment of Water Management Plans," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(7), pages 877-894, July.
    8. Javier Paredes-Arquiola & Joaquín Andreu-Álvarez & Miguel Martín-Monerris & Abel Solera, 2010. "Water Quantity and Quality Models Applied to the Jucar River Basin, Spain," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(11), pages 2759-2779, September.
    9. Zong Woo Geem & Jin-Hong Kim, 2016. "Sustainable Optimization for Wastewater Treatment System Using PSF-HS," Sustainability, MDPI, vol. 8(4), pages 1-13, March.
    10. G. Saharidis & I. Androulakis & M. Ierapetritou, 2011. "Model building using bi-level optimization," Journal of Global Optimization, Springer, vol. 49(1), pages 49-67, January.
    11. Xu, Y. & Huang, G.H. & Qin, X.S. & Cao, M.F., 2009. "SRCCP: A stochastic robust chance-constrained programming model for municipal solid waste management under uncertainty," Resources, Conservation & Recycling, Elsevier, vol. 53(6), pages 352-363.
    12. Li, Y.P. & Huang, G.H. & Zhang, N. & Nie, S.L., 2011. "An inexact-stochastic with recourse model for developing regional economic-ecological sustainability under uncertainty," Ecological Modelling, Elsevier, vol. 222(2), pages 370-379.
    13. Qi Liu & Gengzhong Feng & Giri Kumar Tayi & Jun Tian, 2021. "Managing Data Quality of the Data Warehouse: A Chance-Constrained Programming Approach," Information Systems Frontiers, Springer, vol. 23(2), pages 375-389, April.
    14. Li, Y.P. & Huang, G.H. & Nie, S.L. & Chen, X., 2011. "A robust modeling approach for regional water management under multiple uncertainties," Agricultural Water Management, Elsevier, vol. 98(10), pages 1577-1588, August.
    15. Ghritlahre, Harish Kumar & Prasad, Radha Krishna, 2018. "Application of ANN technique to predict the performance of solar collector systems - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 84(C), pages 75-88.
    16. Gao, Yang & Zhang, Xiao & Wu, Lei & Yin, Shijiu & Lu, Jiao, 2017. "Resource basis, ecosystem and growth of grain family farm in China: Based on rough set theory and hierarchical linear model," Agricultural Systems, Elsevier, vol. 154(C), pages 157-167.
    17. Feifei Dong & Yong Liu & Han Su & Zhongyao Liang & Rui Zou & Huaicheng Guo, 2016. "Uncertainty-Based Multi-Objective Decision Making with Hierarchical Reliability Analysis Under Water Resources and Environmental Constraints," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 805-822, January.
    18. Ling Tan & Ji Guo & Selvarajah Mohanarajah & Kun Zhou, 2021. "Can we detect trends in natural disaster management with artificial intelligence? A review of modeling practices," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 107(3), pages 2389-2417, July.
    19. E. Hernandez & Venkatesh Uddameri, 2010. "Selecting Agricultural Best Management Practices for Water Conservation and Quality Improvements Using Atanassov’s Intuitionistic Fuzzy Sets," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(15), pages 4589-4612, December.
    20. Tao Jiang & Ming Zhong & Ying-jie Cao & Long-jian Zou & Bo Lin & Ai-ping Zhu, 2016. "Simulation of Water Quality under Different Reservoir Regulation Scenarios in the Tidal River," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(10), pages 3593-3607, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jdataj:v:3:y:2018:i:4:p:50-:d:181172. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.