Set pair analysis is a new intelligent algorithm for dealing with complex uncertain problems, and it is widely used in environmental science because of its concise structure and scalability of results. However, it is still unclear about the development stage distribution of set pair analysis in environmental science and the specific development and application in key areas. Therefore, based on the method of bibliometrics, this paper studies the development, application and challenges of set pair analysis in environmental science over the past 32 years (1989–2020). The analysis found that in terms of time dimension, the development process of set pair analysis is divided into three stages: the initial stage (1989–2011); the rapid development stage (2012–2015); the steady development stage (2016 to present). In terms of specific fields, this article focuses on the development and application of set pair analysis in the three fields of ecology, water resources, and atmospheric environmental science. It is found that set pair analysis is mainly used for environmental assessment, diagnosis and prediction. In particular, the development of partial connection numbers is a new research trend of set pair analysis, which plays an important role in environmental assessment, diagnosis and prediction. However, the current set pair analysis also has the shortcomings of strong subjectivity, an imperfect theoretical system, and unbalanced development at home and abroad. Only when these deficiencies are solved, can the development of set pair analysis in environmental science be further promoted.

In semi-arid basins, riparian vegetation is an important part of the river ecosystem. However, with the decrease in river runoff caused by human activities and the continuous changes in climate, riparian vegetation has gradually degraded. To identify the main influencing factors of riparian vegetation changes, we extracted the river flow indicators, climate indicators, and riparian vegetation indicators of a Xiliao River typical section from 1985 to 2020 in spring and summer, and established a random forest model to screen the key driving factors of riparian vegetation. Then, we simulated the response characteristics of riparian vegetation to the key driving factors in spring and summer based on nonlinear equations. The results showed that the contribution of river flow factors to riparian vegetation was higher than that of climate factors. In spring, the key driving factors of riparian vegetation were the average flow in May and the average flow from March to May; in summer, the key driving factors were the average flow in May, the maximum 90-day average flow, and the average flow from March to August. Among them, the average flow in May contributed more than 50% to the indicators of riparian vegetation in both spring and summer. The final conclusion is that in the optimal growth range of plants, increasing the base flow and pulse flow of rivers will promote seed germination and plant growth, but when the river flow exceeds this threshold, vegetation growth will stagnate. The research results improve the existing knowledge of the influencing factors of riparian vegetation in semi-arid basins, and provide a reference for improving the natural growth of riparian vegetation and guiding the ecological protection and restoration of rivers in semi-arid areas.