An Ontology-based Knowledge Modelling Approach for River Water Quality Monitoring and Assessment

Zhu, Xiaomin; Yi, Jianjun; Huang, Xiaoci; Chen, Shaoli

doi:10.1016/j.procs.2016.08.146

Cited by 17 publications

(8 citation statements)

References 12 publications

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“…As in [5], the authors [6] discuss the possibilities of using new information technologies, but do not offer specific solutions with the description of models and algorithms of situation recognition. The paper [7] describes the ontology model that is designed for river water quality monitoring. At the same time, it is possible to present the semantic properties of river water quality data and build semantic value among various concepts related to river water quality monitoring.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Development of decision support in the structure of the informationanalytical system of atmospheric air environmental monitoring

Kortsova

Bakharev

Shevchenko

et al. 2018

EEJET

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Section: Literature Review and Problem Statementmentioning

confidence: 99%

Development of decision support in the structure of the informationanalytical system of atmospheric air environmental monitoring

Kortsova

Bakharev

Shevchenko

et al. 2018

EEJET

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“…7. An Ontology-based Knowledge Modelling Approach for River Water Quality Monitoring and Assessment (2016) [11]. The authors present an ontology of the modeling to evaluate water quality in a river, depict the data of water quality and make the semantic relevance between the concepts involved.…”

Section: Doc 5 a Wireless Sensor Network Based Watermentioning

confidence: 99%

Water Quality Monitoring Systems Based on Intelligent Agents: A Systematic Literature Review

Osorio¹,

Barrera²,

Soto³

et al. 2018

RCS

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Water is a vital resource for life; however, although most of the planet is covered with water, only a small percentage corresponds to fresh water. Also, a low percentage of fresh water corresponds to drinking water, that is, water useful for human consumption. Despite this, the society has been contaminating the sources of fresh water, reducing more and more the amount of water available for human use. This paper presents a systematic literature review on the various modern mechanisms to monitor water quality, through the use of technology to take measurements and the use of storage devices. A comparison is made between studies regarding in this topic and a set of stands of work is proposed to be developed in the future. This review may guide the reader about the basis of available of information and communication technologies and their application in management systems to monitor water quality, in order to facilitate the search for planning and design of sustainable new system.

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“…Water quality monitoring (WQM) is a technical term and good example of this scientific endeavor in the realm of water research (Sanders et al, 1983;Chapman, 1996). The main purposes of WQM include understanding of watershed health and dynamic, current conditions and trends in the surface water system, and providing reliable information to help decision-makers to interpret and manage the stakeholders' health risk (Park et al, 2006;Baltacı et al, 2008;Telci et al, 2009;Xiaomin et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

A novel approach for selecting sampling points locations to river water quality monitoring in data-scarce regions

Alilou

Nia

Saravi

et al. 2019

Journal of Hydrology

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In order to rationalize a surface water quality monitoring network (WQMN), it is critical to appropriately design surface water quality sampling locations. This is due to high installation, operational, and maintenance costs for each sampling representative of the whole water system conditions. The main objective of this study was to propose an integrated method to determine the most appropriate sampling points in the Khoy watershed northwest of Iran, where financial 2 resources and water quality data are limited. Multi criteria evaluation method including analytic network process (ANP) and Fuzzy logic were incorporated in River Mixing Length (RML) procedure in order to identify exact locations of sampling points. Based on RML procedure, 15 candidate sampling points were identified to suitably select sampling points based on budget deficiency. Relative weights for 12 criteria and 10 sub-criteria related to non-point sources and surficial rocks as well as criteria of topography were then calculated by the ANP method. According to the obtained results, a new total potential pollution score (TPPS) was presented to prioritize 15 candidate sampling points. Then, the values of TPPS were classified and fuzzified to distinguish real differences between scores. Based on current monitoring stations and budget deficiency, the hierarchy value, and Fuzzy rank, six points are proposed as the most appropriate locations for surface water quality monitoring. Furthermore, four points are identified as the second most appropriate for enhancing a robust WQMN in the study area in order for an expansion plan in the future. The results of this study should be valuable for water quality monitoring agencies looking for a cost-effective approach for selecting exact sampling locations.

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An Ontology-based Knowledge Modelling Approach for River Water Quality Monitoring and Assessment

Cited by 17 publications

References 12 publications

Development of decision support in the structure of the informationanalytical system of atmospheric air environmental monitoring

Development of decision support in the structure of the informationanalytical system of atmospheric air environmental monitoring

Water Quality Monitoring Systems Based on Intelligent Agents: A Systematic Literature Review

A novel approach for selecting sampling points locations to river water quality monitoring in data-scarce regions

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An Ontology-based Knowledge Modelling Approach for River Water Quality Monitoring and Assessment

Cited by 17 publications

References 12 publications

Development of decision support in the structure of the information­analytical system of atmospheric air environmental monitoring

Development of decision support in the structure of the information­analytical system of atmospheric air environmental monitoring

Water Quality Monitoring Systems Based on Intelligent Agents: A Systematic Literature Review

A novel approach for selecting sampling points locations to river water quality monitoring in data-scarce regions

Contact Info

Product

Resources

About

Development of decision support in the structure of the informationanalytical system of atmospheric air environmental monitoring

Development of decision support in the structure of the informationanalytical system of atmospheric air environmental monitoring