Investigating river health and potential risks using a novel hybrid decision-making framework with multi-source data fusion in the Qinghai-Tibet Plateau

Abstract

River health assessment (RHA) is a powerful tool for examining river health and provides promising solutions for ecological conservation and sustainable river management. However, currently available methods still fail to consider the superimposed effects of randomness and fuzziness on RHA. Additionally, the existing RHA studies mainly focus on the plains and lack detailed investigations in the Qinghai-Tibet Plateau (QTP). Terrain, climate, natural hazards and human activities contribute to the inherent fragility and inevitable uncertainty of rivers in the QTP. This study proposed a novel intuitionistic fuzzy cloud (IFC) by coupling the intuitionistic fuzzy sets and cloud model. A new hybrid decision-making framework based on IFC algorithm was then developed to facilitate the RHA with fuzziness and randomness. To deeply investigate river health in the QTP, the Lhasa River (LR) was chosen as a typical study area. We formulated an indicator system with multi-source data fusion, and used the geodetector technique to explore the drivers and potential risks associated with river health. Results showed that the developed research framework addressed the shortcomings of conventional techniques, expanded the capabilities of existing models, and offered a potentially promising approach to RHA with fuzziness and randomness. In LR, health statuses of evaluation indicators were unsatisfactory, with healthy compliance rates of 100%, 62.5% and 37.5% in the upper, middle and lower reaches, respectively. Meanwhile, health statuses demonstrated substantial spatial variation in LR. Excellent, healthy and subhealthy sampling sites accounted for approximately 28%, 24% and 48% of the total. Our results highlight that dam construction, urbanization and fish release have posed potential risks to the LR health, and appropriate measures should be developed immediately to mitigate their impacts on ecologically fragile areas.