| 16 Jul 2026
Review article: Global flood research across four decades: An analysis of 57,474 research articles based on a large language model
Abstract. The proliferation of research literature has resulted in increasingly fragmented information and diversified knowledge structures, making it increasingly difficult to develop a systematic understanding of disciplinary research systems. This study employed a large language model to screen and organize flood research articles from 1985 to 2024, provided visual spatiotemporal insights into the quantity and quality of publications, contributions of institutions and countries, evolution of keywords, research types and topics, as well as the geographic characteristics of river basin and urban units. Findings indicate that annual publications on flood studies now exceed 5,500, with the average number of authors and institutions per publication increasing from 2.1 to 4.8 and from 1.4 to 2.6, respectively. Chinese and American institutions lead in publication quantity, while European and American institutions dominate in research influence. The disciplines of climate and remote sensing have gradually gained an undeniable influence in flood research field. The evolution of keywords focus traces a conceptual progression from “ecological-hydrological system interactions,” through “hydrological and hydrodynamic processes analysis” and “flood disaster prevention and management,” to “flood prediction and risk assessment under climate change.” River flood remains a consistent focus (averaging 55 % of research), while urban flood has seen a notable rise in attention (increasing from 8 % to 15 % over the past decade). Research topics concentrate on management, simulation, monitoring, and risk assessment. River basin flood research has evolved from Mississippi River Basin leadership to bipolar dominance with the Yangtze River Basin. Urban flood research has shifted from leadership by Texas in the United States to a dual-core structure with Guangdong Province in China. This study aims to advance the application of large language models in flood research literature review, thereby enabling a more systematic and efficient understanding of the comprehensive characteristics of the field’s development.
The study relies on Gemma 3-27B to identify relevant articles and extract study locations, flood types, topics, methods, institutions, and countries. Because these outputs form the basis of the results, the authors should explain how their reliability was verified.
The Introduction discusses earlier LLM-assisted reviews, including a study analysing 310,000 hydrology publications. The authors should explain more clearly how the present manuscript differs from previous large-scale hydrological literature reviews.
The definitions of several flood categories require clarification. For example, coastal storm surge, tsunami, ice flood, snowmelt flood, and mountain flood may overlap. The prompt also describes the task as multi-label classification but instructs the model to avoid multiple categories whenever possible.
Some interpretations connect publication patterns directly to policies, disasters, economic development, and major infrastructure projects. For example, the manuscript links research changes to the Rio Earth Summit, the EU Water Framework Directive, the Three Gorges Project, Hurricane Katrina, and the Sponge City initiative. These explanations may be reasonable, but the analysis mainly demonstrates temporal associations. The wording should therefore be more cautious. Expressions such as “may have contributed,” “coincided with,” or “could partly explain” would be more appropriate than direct causal statements. The terms “economically driven basins” and “religiously driven basins” should also be reconsidered. The description of the Indus and Ganges as “religiously driven” is broad and may oversimplify complex hydrological, political, economic, and cultural conditions. More neutral and evidence-based terminology is recommended.
The conclusion mainly repeats the descriptive findings. It should more clearly explain how the results can guide future flood research.
The manuscript contains valuable maps, networks, word clouds, and multi-panel figures, but several labels are small and difficult to read. The geographical figures in particular contain many panels, abbreviated locations, small legends, and crowded labels.