AI Uncovers Two Decades of Evolution in China’s Hydrological Research: A Novel Large Language Model Approach

Over the past three decades, China's unprecedented economic growth and rapid urbanization have brought major challenges in water resource management, flood control, and ecological protection. This demand has driven a rapid expansion and evolution in hydrological research. However, the exponential growth of scientific literature makes it increasingly difficult for individual researchers to quantitatively grasp the field's development and shifting trends, particularly when trying to extract specific geographic locations or thematic nuances from publication abstracts.

In a study published in Fundamental Research by a team of researchers led by Professor Chiyuan Miao from Beijing Normal University, a fine-tuned Large Language Model paired with geocoding tools to automatically "read" and parse complex basin information from 289,513 global publications was deployed. 

"Traditional reviews inherently reflect qualitative assessments shaped by researchers' personal expertise and perspectives," explains Miao. "Leveraging advanced artificial intelligence techniques, such as LLM and topic modeling, we have achieved automated processing at an unprecedented scale, isolating 4,177 highly relevant studies specifically focusing on China’s major basins."

The team's extensive data analysis highlights several crucial milestones in the development of Chinese hydrology

1. Surging Research Output & Collaboration: Chinese hydrology publications have significantly increased. Scientific collaboration has also deepened, with the average number of authors per paper rising by 0.9 authors per decade.

2. Dominant Hydrological Models: The Soil and Water Assessment Tool (SWAT) leads with a 46.7% usage rate, closely followed by the Variable Infiltration Capacity (VIC) model at 15.7%, and the domestically developed Xinanjiang (XAJ) model at 11.9%. This highlights a research landscape that balances international integration with regional adaptability.

3. Shifting Research Focus: The analysis identified "water resources" (13.9%), "climate change" (13.6%), and "hydrological modeling" (10.8%) as the primary research topics. Notably, the discipline has shifted from a "resource hydrology" phase (2000–2010), focused on water development and management, to an "eco-hydrology" phase (2011–present), prioritizing climate change, carbon dynamics, and ecological protection.

4. Basin Attention: The Yangtze River Basin and the Yellow River Basin have garnered the most scientific accounting for approximately 34.8% and 20.6% of the total basin-specific publications, respectively. This focus directly aligns with their crucial economic status, ecological vulnerability, and national strategic initiatives.

The team hopes their AI-empowered approach will not only trace the historical trajectory of Chinese hydrology but also guide future research priorities and sustainable water resource strategies worldwide.

Contact author:

Chiyuan Miao, State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China, miaocy@bnu.edu.cn

Funder: 

The authors acknowledge the financial support from National Natural Science Foundation of China (U24A20572, 42342023), and the National Key Research and Development Program of China (2024YFF0809301).

Conflict of interest: 

The authors declare that they have no conflicts of interest in this work.

See the article: 

Hu, J., Miao, C., Wu, Y., & Su, J. Advances in hydrological research in China over the past two decades: Insights from advanced large language model and topic modeling[J]. Fundamental Research. https://doi.org/10.1016/j.fmre.2025.05.002