模型在湖泊咸化研究中的应用:研究现状与展望

Applications of models in lake salinization research: Current status and prospects

摘要

【目的】湖泊咸化在全球气候变化与人类活动影响下日益严峻,对生态和水资源造成严重威胁。为了更好地了解模型在湖泊咸化研究领域的研究现状,总结研究趋势。【方法】本研究运用文献计量工具VOSviewer,以Web of Science核心合集数据库为数据来源,对1900年至今湖泊咸化与模型研究领域的文献进行计量分析。【结果】结果显示:文献计量可视化结果呈现明显阶段性变化趋势,该领域在多个研究方向呈现交叉特点,总结形成该领域的热点话题,并根据关键词突变结果解析研究趋势形成展望。结果表明,该领域发展历经缓慢探索期、平稳发展期和快速增长期,2009年后受气候变化研究热潮影响,发文量快速增长,未来预计持续上升。研究热点集中于生态系统、环境变化和水模型等领域。关键词分析表明,研究正朝着综合化方向发展,多学科知识与方法的整合愈发关键。在未来,高海拔与干旱地区(如青藏高原和新疆)的湖泊咸化问题将受到更多关注,遥感、机器学习等新兴技术将广泛应用于湖泊盐度演变分析与水资源管理,推动该领域研究进一步深入。【结论】全面梳理了该领域在水文学、地质学和生态学的研究现状,明确了研究热点与趋势,为湖泊生态保护和水资源可持续利用提供科学依据。

Abstract

[Objective] Lake salinization has become increasingly severe due to global climate change and human activities,posing significant threats to ecosystems and water resources. The aims are to evaluate the current status of model research on lake salinization and summarize research directions. [Methods] Bibliometric tool VOSviewer was employed, with Web of Science Core Collection database serving as the data source, to conduct a quantitative analysis of publications in the field of lake salinization and model research spanning from 1900 to present. [Results] The result showed that the bibliometric visualization exhibited distinct phased changes. The research domain showed interdisciplinary characteristics across multiple directions. Key research hotspots were systematically summarized, and future trends were projected based on keyword burst detection analysis. The results demonstrated that the field went through three developmental phases: a slow exploration phase, a stable development phase, and a rapid growth phase. Since 2009, influenced by heightened interest in climate change research, the volume of publications surged with sustained increases projected for the future. Research hotspots included ecosystem dynamics, environmental variation, and hydrological modeling. Keyword burst analysis highlighted a transition toward integrated research, with interdisciplinary knowledge synthesis and methodological integration becoming increasingly crucial. Future research is anticipated to focus on salinization in high-altitude and arid regions(e. g., Qinghai-Xizang Plateau and Xinjiang). Cutting-edge technologies such as remote sensing and machine learning are expected to be widely applied for salinity dynamics analysis and water resource management, thereby promoting advancements in this field. [Conclusion] Current research status of this field across hydrological, geological, and ecological disciplines is comprehensively reviewed, with research hotspots and emerging trends identified, providing a scientific foundation for ecological conservation and sustainable water resource utilization in lakes.

关键词

湖泊咸化 / 文献计量 / 模型研究 / 气候变化 / 研究热点 / 影响因素

Key words

lake salinization / bibliometrics / model research / climate change / research hotspots / influencing factors

基金资助

内蒙古自治区水利科技项目(NSK202403)

北京师范大学博一学科交叉基金项目(BNUXKJC2425)

国家重点研发计划项目(2019YFC0409201)