气候变化领域集成服务门户(CCPortal): River ecosystem health assessment in the Qinghai-Tibet Plateau: A novel hybrid method based on artificial intelligence and multi-source data fusion

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DOI	10.1016/j.eswa.2024.124078
	River ecosystem health assessment in the Qinghai-Tibet Plateau: A novel hybrid method based on artificial intelligence and multi-source data fusion
	Zhang, Zhengxian; Wang, Xiaogang; Li, Yun; Liu, Yi; Xu, Yuan; Li, Jingjuan; Ding, Wenhao; Li, Hongze; Yang, Hong
发表日期	2024
ISSN	0957-4174
EISSN	1873-6793
起始页码	251
卷号	251
英文摘要	River ecosystem health assessment (REHA), an effective approach for identifying river ecosystem health, is crucial for achieving sustainable river management and ensuring water security. However, existing REHA methods still fail to consider the cumulated influences of uncertain inputs, stochastic environment and limited rationality of decision makers on REHA. Additionally, current REHA studies have mainly concentrated on plain areas, while the Qinghai-Tibet Plateau (QTP) remains largely unknown. Developing REHA techniques for plateau rivers is an urgent matter, due to the heightened fragility and complexity of river ecosystems in the QTP. To accurately assess river ecosystem health in the QTP, this study proposed Pythagorean fuzzy cloud (PFC) via coupling the Pythagorean fuzzy sets and cloud model. A novel PFC-TODIM model was developed by extending TODIM (the acronym in Portuguese for interactive and multicriteria decision making) to the Pythagorean fuzzy environment. The hybrid decision making framework was then created to handle REHA with uncertain inputs and stochastic environment, and the Senge Tsangpo River (STR) served as a case study in the QTP. We developed the indicator system based on multi-source data fusion, and employed Bayesian model averaging (BMA) method to reveal the potential risks and driving factors of river ecosystem health. Results showed that the developed models considered the limited rationality of decision makers, effectively handled REHA with uncertainties, and avoided overestimating river health levels due to ignoring the randomness and fuzziness of REHA. In STR, health statuses exhibited marked spatial differences. Sampling sites of 9.091%, 77.273 % and 13.636 % were excellent, healthy and subhealthy, respectively. Our findings highlight that dams, urban development, fish release, and grazing have adverse impacts on STR health, and effective protection measures are required to minimize human interferences on ecologically fragile areas. These findings can improve our understanding of the human disturbances and natural factors that interfere with river ecosystem health in the QTP.
英文关键词	River ecosystem health assessment; Cloud model; Pythagorean fuzzy sets; Hybrid method; Qinghai-Tibet Plateau
语种	英语
WOS研究方向	Computer Science ; Engineering ; Operations Research & Management Science
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Operations Research & Management Science
WOS记录号	WOS:001235191500001
来源期刊	EXPERT SYSTEMS WITH APPLICATIONS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/287752
作者单位	Nanjing Forestry University; Nanjing Forestry University; Nanjing Hydraulic Research Institute; Nanjing University; Sichuan University; University of Reading
推荐引用方式 GB/T 7714	Zhang, Zhengxian,Wang, Xiaogang,Li, Yun,et al. River ecosystem health assessment in the Qinghai-Tibet Plateau: A novel hybrid method based on artificial intelligence and multi-source data fusion[J],2024,251.
APA	Zhang, Zhengxian.,Wang, Xiaogang.,Li, Yun.,Liu, Yi.,Xu, Yuan.,...&Yang, Hong.(2024).River ecosystem health assessment in the Qinghai-Tibet Plateau: A novel hybrid method based on artificial intelligence and multi-source data fusion.EXPERT SYSTEMS WITH APPLICATIONS,251.
MLA	Zhang, Zhengxian,et al."River ecosystem health assessment in the Qinghai-Tibet Plateau: A novel hybrid method based on artificial intelligence and multi-source data fusion".EXPERT SYSTEMS WITH APPLICATIONS 251(2024).