|国家科技期刊平台
首页|期刊导航|人民珠江|基于CiteSpace知识图谱的水文大数据研究进展

基于CiteSpace知识图谱的水文大数据研究进展OA

Research Progress of Hydrological Big Data Based on CiteSpace Knowledge Graph

中文摘要英文摘要

水文大数据相关研究是近些年水文领域的研究重点和核心问题,同时也是提高水文事务处理效率和增强水文规律真实性及可信性的重要内容.现将从中国知网(CNKI)收录的264 篇文献和Web of Science(WOS)收录的219 篇文献作为样本数据,利用CiteSpace软件对其进行研究人员、研究机构及热点分析,深入探索该领域研究的发展趋势.研究表明:从发文量总体来看,国内和国际发文量均呈现上升趋势.从研究人员和研究机构来看,国内学者和机构间呈现"大分散,小聚集"的现象.从研究热点来看,以"智慧水文""预警系统""Big data testing"等为突现关键词意味着该领域的研究重点逐渐向技术化、数字化方向演进,无论在国内还是国际,现代的水文监测技术与水文学方法相对于传统的技术和方法,均具有更高的准确性和稳定性,可以更充分地满足实际应用需求,将水文和大数据相结合逐渐成为了该领域的研究趋势.

Research related to hydrological big data has been a focal point and core issue in the field of hydrology in recent years.It is also an important component for improving the efficiency of hydrological affairs processing and enhancing the authenticity and credibility of hydrological patterns.This study utilized a sample dataset comprising 264 papers collected from China Knowledge Infrastructure(CNKI)and 219 papers collected from Web of Science(WOS).Using CiteSpace software,this paper analyzed the researchers,institutions,and research hotspots and explored the development trend of research in this field in depth.The findings indicate that,overall,both Chinese and international publications show an increasing trend.Regarding researchers and research institutions,there is a phenomenon of"large scattering and small gathering"among Chinese scholars and institutions.Examining research hotspots reveals that keywords such as"intelligent hydrology,""early warning system,""big data testing"signify that the focus of research in this field is gradually shifting towards technological and digital directions.Whether domestically or internationally,modern hydrological monitoring technologies and hydrological methods,in comparison to traditional technologies and methods,demonstrate higher accuracy and stability.They can more fully meet the practical application requirements,and the combination of hydrology and big data has gradually become a research trend in this field.

孟露;杨海波

郑州大学水利与土木工程学院,河南 郑州 450001

地球科学

CiteSpace知识图谱水文大数据可视化分析

CiteSpaceknowledge graphhydrological big datavisual analysis

《人民珠江》 2024 (002)

38-44 / 7

国家重点研发项目(2021YFC3200200)

10.3969/j.issn.1001-9235.2024.02.005

评论