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Hydrological Research Evolution: A Large Language Model-Based Analysis of 310,000 Studies Published Globally Between 1980 and 2023

Miao, Chiyuan (författare)
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing, China
Hu, Jinlong (författare)
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing, China
Moradkhani, Hamid (författare)
Department of Civil, Construction and Environmental Engineering, University of Alabama, Tuscaloosa, AL, USA; Center for Complex Hydrosystems Research, University of Alabama, Tuscaloosa, AL, USA
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Destouni, Georgia, 1961- (författare)
KTH,Vatten- och miljöteknik,Department of Physical Geography, Stockholm University, Stockholm, Sweden; Stellenbosch Institute for Advanced Study, Stellenbosch, South Africa
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 (creator_code:org_t)
American Geophysical Union (AGU), 2024
2024
Engelska.
Ingår i: Water resources research. - : American Geophysical Union (AGU). - 0043-1397 .- 1944-7973. ; 60:6
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • Hydrology plays a crucial role in understanding Earth's intricate water system and addressing water-related problems, including against the backdrop of ongoing climate change. A retrospective review of the evolution of hydrology up to the current state of research is of great importance for understanding this role. While there have been some quantitative reviews of large numbers of hydrological publications, there still remains a lack of overarching hydrological research assessment, particularly with the focus on hydrological basins as fundamental spatial-geographic units of hydrological analysis. Large language models, represented by OpenAI's ChatGPT, have demonstrated powerful textual understanding capabilities, making it possible to extract such overarching and basin information from hydrological publications. Here, we considered publications related to hydrology from Web of Science spanning January 1980 to October 2023, and parsed the information from this extensive body of literature by integrating a large language model and geocoding. These techniques enable quantitative analysis of research characteristics across different spatio-temporal scales, focusing on hotspot topics, collaboration networks, and various basins worldwide. Our study revealed an increase in hydrological research since the 1990 s, with shifts in research priorities from groundwater and nutrients to climate change and ecohydrology. Some basins in North America and Europe have consistently been hotspots for hydrological research. Since the 2010s, there has been a noteworthy increase in interest toward basins in China and South Asia, but attention to many regions with frequent extreme rainfall remains insufficient. Geographical patterns show different preferred research topics for different basins, but climate change has emerged as the most prominent topic across all regions in the last decade. In conclusion, our study provides an effective approach to quantitative analysis of research trends, offering a fresh view on the evolution of hydrology as a research field, its focus on various hydrological basins around the world, and the emergence of overarching and basin-specific hot topics over time.

Ämnesord

NATURVETENSKAP  -- Geovetenskap och miljövetenskap -- Oceanografi, hydrologi och vattenresurser (hsv//swe)
NATURAL SCIENCES  -- Earth and Related Environmental Sciences -- Oceanography, Hydrology and Water Resources (hsv//eng)

Nyckelord

bibliometric analysis
geographic research assessment
global publications
hydrological basins
hydrological research
large language models

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