智慧水文研究中知识图谱可视化分析

Visualization Analysis of Research Knowledge Graph for Smart Hydrology

摘要:

为充分了解智慧水文的研究进展与现状,基于2010—2024年中国知网(CNKI)中“智慧水文”相关研究文献,采用文献计量和可视化的方法,利用CiteSpace软件构建关键词共现、聚类、时间线、突现词的各类可视化知识图谱,明确研究领域的时间脉络、热点演变和发展趋势。结果表明:智慧水文相关发文量逐年增长,其发展与国家政策息息相关,2017年开始出现快速发展趋势;经聚类分析与时间线推演发现,智慧水文的技术发展依然是未来主要研究方向,水文、智慧水文、数字流域、智慧水利是主要聚类群体,且共被引程度较高;国内智慧水文的研究需要向数字孪生、“四预”等新方向继续深化;知识图谱构建可以对复杂的水文问题进行可视化分析与展示,提高研究效率与质量。

Abstract:

To fully understand the research progress and status of smart hydrology, based on the relevant research literature on "smart hydrology" from CNKI during 2010—2024, this paper adopts bibliometric and visualization methods, and uses CiteSpace software to construct various visual knowledge maps of keyword co-occurrence, clustering, timeline, and burst terms, so as to clarify the temporal context, hotspot evolution, and development trends of the research field. The results show that the number of publications related to smart hydrology has increased year by year, and its development is closely related to national policies, showing a rapid development trend since 2017. Through cluster analysis and timeline deduction, it is found that the technological development of smart hydrology will remain the mainstream research direction in the future. Hydrology, smart hydrology, digital watershed, and smart water resources are the main clustering groups with a high degree of co-citation. Domestic research on smart hydrology needs to be further deepened in new directions such as digital twin and "Four Preventions". The construction of knowledge graphs can realize visual analysis and display of complex hydrological problems, improving research efficiency and quality.