Developing a Novel Robust Model to Improve the Accuracy of River Ecosystem Health Assessment in the Qinghai–Tibet Plateau

Yuan Xu, Yun Li (), Xiaogang Wang (), Jianmin Zhang and Zhengxian Zhang
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Yuan Xu: State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu 610065, China
Yun Li: State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing 210029, China
Xiaogang Wang: State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing 210029, China
Jianmin Zhang: State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu 610065, China
Zhengxian Zhang: Key Laboratory of Integrated Regulation and Resource Development on Shallow Lake of Ministry of Education, College of Environment, Hohai University, Nanjing 210098, China

Sustainability, 2025, vol. 17, issue 5, 1-24

Abstract: River ecosystem health assessment (REHA) is crucial for sustainable river management and water security. However, existing REHA methodologies still fail to consider the multiple effects of input uncertainty, environmental stochasticity, and the decision-maker’s bounded rationality. Moreover, REHA studies primarily focused on plain areas, leaving the Qinghai–Tibet Plateau (QTP) understudied despite its ecosystems’ heightened fragility and complexity. To address these gaps, this study combined Pythagorean fuzzy sets with cloud modeling and proposed the Pythagorean fuzzy cloud (PFC) approach. Accordingly, a novel robust model (PFC-TODIM) was created by expanding the conventional TODIM method to the PFC algorithm. We provided an REHA indicator system tailored to the distinctive characteristics in the QTP, leveraging multisource data. River ecosystem health, driving mechanisms, and potential threats were investigated in the Lhasa River (LR) using the PFC-TODIM model. Results showed that the created model effectively took multiple uncertainties into consideration, thereby improving the REHA accuracy and robustness. In the LR, health conditions demonstrated substantial spatial disparities. Sampling sites of 28%, 48%, and 24% were subhealthy, healthy, and excellent, respectively. Findings showed that anthropogenic factors, such as dams, urban development, and fish release adversely affect river health and should be properly managed.

Keywords: river ecosystem health; Qinghai-Tibet Plateau; Pythagorean fuzzy cloud; robust model; multiple uncertainties (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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