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An Ontology-Underpinned Emergency Response System for Water Pollution Accidents

Author

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  • Xiaoliang Meng

    (School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China)

  • Chao Xu

    (School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China)

  • Xinxia Liu

    (School of Water Conservancy and Electric Power, Hebei University of Engineering, 62#Zhonghua Street, Handan 056038, China)

  • Junming Bai

    (School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China)

  • Wenhan Zheng

    (Fujian Surveying and Mapping Institute, Fuzhou 350003, China)

  • Hao Chang

    (School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China)

  • Zhuo Chen

    (School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China)

Abstract

With the unceasing development and maturation of environment geographic information system, the response to water pollution accidents has been digitalized through the combination of monitoring sensors, management servers, and application software. However, most of these systems only achieve the basic and general geospatial data management and functional process tasks by adopting mechanistic water-quality models. To satisfy the sustainable monitoring and real-time emergency response application demand of the government and public users, it is a hotspot to study how to make the water pollution information being semantic and make the referred applications intelligent. Thus, the architecture of the ontology-underpinned emergency response system for water pollution accidents is proposed in this paper. This paper also makes a case study for usability testing of the water ontology models, and emergency response rules through an online water pollution emergency response system. The system contributes scientifically to the safety and sustainability of drinking water by providing emergency response and decision-making to the government and public in a timely manner.

Suggested Citation

  • Xiaoliang Meng & Chao Xu & Xinxia Liu & Junming Bai & Wenhan Zheng & Hao Chang & Zhuo Chen, 2018. "An Ontology-Underpinned Emergency Response System for Water Pollution Accidents," Sustainability, MDPI, vol. 10(2), pages 1-18, February.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:2:p:546-:d:132483
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    References listed on IDEAS

    as
    1. Rabia Koklu & Bulent Sengorur & Bayram Topal, 2010. "Water Quality Assessment Using Multivariate Statistical Methods—A Case Study: Melen River System (Turkey)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(5), pages 959-978, March.
    2. Xue Wang & Yong Pang & Xiao Wang & Qi Zhou & Rongrong Xie, 2017. "Study of Water Environmental Cumulative Risk Assessment Based on Control Unit and Management Platform Application in Plain River Network," Sustainability, MDPI, vol. 9(6), pages 1-16, June.
    3. Manhong Shen & Yongliang Yang, 2017. "The Water Pollution Policy Regime Shift and Boundary Pollution: Evidence from the Change of Water Pollution Levels in China," Sustainability, MDPI, vol. 9(8), pages 1-22, August.
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    Cited by:

    1. Mingjing Guo & Ziyu Jiang & Yan Bu & Jinhua Cheng, 2019. "Supporting Sustainable Development of Water Resources: A Social Welfare Maximization Game Model," IJERPH, MDPI, vol. 16(16), pages 1-15, August.
    2. Juan Du & Hengqing Jing & Kim-Kwang Raymond Choo & Vijayan Sugumaran & Daniel Castro-Lacouture, 2020. "An Ontology and Multi-Agent Based Decision Support Framework for Prefabricated Component Supply Chain," Information Systems Frontiers, Springer, vol. 22(6), pages 1467-1485, December.
    3. Anat Goldstein & Lior Fink & Gilad Ravid, 2021. "A Framework for Evaluating Agricultural Ontologies," Sustainability, MDPI, vol. 13(11), pages 1-12, June.
    4. Juan Du & Hengqing Jing & Kim-Kwang Raymond Choo & Vijayan Sugumaran & Daniel Castro-Lacouture, 0. "An Ontology and Multi-Agent Based Decision Support Framework for Prefabricated Component Supply Chain," Information Systems Frontiers, Springer, vol. 0, pages 1-19.
    5. Kwoting Fang & Shuoche Lin, 2019. "An Integrated Approach for Modeling Ontology-Based Task Knowledge on an Incident Command System," Sustainability, MDPI, vol. 11(12), pages 1-26, June.
    6. Zaenal Akbar & Hani Febri Mustika & Dwi Setyo Rini & Lindung Parningotan Manik & Ariani Indrawati & Agusdin Dharma Fefirenta & Tutie Djarwaningsih, 2021. "An Ontology-Driven Personalized Faceted Search for Exploring Knowledge Bases of Capsicum," Future Internet, MDPI, vol. 13(7), pages 1-17, June.

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