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An Ontology-Underpinned Emergency Response System for Water Pollution Accidents

School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
School of Water Conservancy and Electric Power, Hebei University of Engineering, 62#Zhonghua Street, Handan 056038, China
Fujian Surveying and Mapping Institute, Fuzhou 350003, China
Author to whom correspondence should be addressed.
Sustainability 2018, 10(2), 546;
Received: 23 January 2018 / Revised: 17 February 2018 / Accepted: 17 February 2018 / Published: 20 February 2018
(This article belongs to the Special Issue Methodological Advances in Research on Sustainable Ecosystems)
PDF [4577 KB, uploaded 25 February 2018]


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. View Full-Text
Keywords: ontology; emergency response system; water pollution accident; reasoning; models ontology; emergency response system; water pollution accident; reasoning; models

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Meng, X.; Xu, C.; Liu, X.; Bai, J.; Zheng, W.; Chang, H.; Chen, Z. An Ontology-Underpinned Emergency Response System for Water Pollution Accidents. Sustainability 2018, 10, 546.

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