Study on river health assessment based on a fuzzy matter-element extension model. (August 2021)
- Record Type:
- Journal Article
- Title:
- Study on river health assessment based on a fuzzy matter-element extension model. (August 2021)
- Main Title:
- Study on river health assessment based on a fuzzy matter-element extension model
- Authors:
- Shan, Chengju
Dong, Zengchuan
Lu, Debao
Xu, Cundong
Wang, Hui
Ling, Zhe
Liu, Qing - Abstract:
- Highlights: The Combined Weight-assignment Method can calculate the weight more comprehensively. Fuzzy matter-element extension has a better capacity in river health assessment. Fuzzy matter-element extension has better capacities in uncertainty analysis and risk recognizing. Abstract: In order to facilitate watershed management, we developed an expansive river health assessment method based on a fuzzy matter-element extension model in this study that developed based on the transitive hierarchies and degree of membership from improved fuzzy optimization theory. Eight characteristics of river flow, namely, the morphology, flow, water quality, river habitat, aquatic organisms, riparian zone, flood control safety, and level of the water supply, were investigated in this study to establish a system of indices to assess river health. We apply the above method to a river health assessment in the Luanhe River as sub-healthy. The results show that the method is accurate for the river health assessment compared with the actual conditions in Luanhe river. Moreover, the river health assessment method described in this study covers the different health states of river ecosystems, including the natural function and the social service function of a river. It is a reasonable river health assessment method that can evaluate river health status systematically, comprehensively and accurately. Therefore, this method is reasonable and effective and can be used to assess the ecological health ofHighlights: The Combined Weight-assignment Method can calculate the weight more comprehensively. Fuzzy matter-element extension has a better capacity in river health assessment. Fuzzy matter-element extension has better capacities in uncertainty analysis and risk recognizing. Abstract: In order to facilitate watershed management, we developed an expansive river health assessment method based on a fuzzy matter-element extension model in this study that developed based on the transitive hierarchies and degree of membership from improved fuzzy optimization theory. Eight characteristics of river flow, namely, the morphology, flow, water quality, river habitat, aquatic organisms, riparian zone, flood control safety, and level of the water supply, were investigated in this study to establish a system of indices to assess river health. We apply the above method to a river health assessment in the Luanhe River as sub-healthy. The results show that the method is accurate for the river health assessment compared with the actual conditions in Luanhe river. Moreover, the river health assessment method described in this study covers the different health states of river ecosystems, including the natural function and the social service function of a river. It is a reasonable river health assessment method that can evaluate river health status systematically, comprehensively and accurately. Therefore, this method is reasonable and effective and can be used to assess the ecological health of rivers in other regions. … (more)
- Is Part Of:
- Ecological indicators. Volume 127(2021)
- Journal:
- Ecological indicators
- Issue:
- Volume 127(2021)
- Issue Display:
- Volume 127, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 127
- Issue:
- 2021
- Issue Sort Value:
- 2021-0127-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-08
- Subjects:
- River ecosystem -- Fuzzy matter-element extension model -- Health assessment -- Luanhe River
Environmental monitoring -- Periodicals
Environmental management -- Periodicals
Environmental impact analysis -- Periodicals
Environmental risk assessment -- Periodicals
Sustainable development -- Periodicals
333.71405 - Journal URLs:
- http://www.sciencedirect.com/science/journal/1470160X/ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.ecolind.2021.107742 ↗
- Languages:
- English
- ISSNs:
- 1470-160X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3648.877200
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 18243.xml