Abstract Hydronyms directly reflect the interactive relationship between humans and water systems. However, research on the spatial distribution patterns and influencing mechanisms of regional hydronyms remains insufficiently systematic, with a notable lack of empirical studies. This paper investigates the spatial distribution characteristics of 10,577 hydronyms in 36 cities along the Grand Canal of China. Methodologically, we innovatively integrated Large Language Models (LLMs) for automated semantic classification with spatial econometric models. We applied the nearest neighbour index (NNI), kernel density estimation (KDE), spatial autocorrelation analysis, and geographically weighted regression (GWR) to examine their spatial patterns and driving factors. The findings reveal that: (1) Hydronyms along the Grand Canal exhibit a clustered spatial pattern, with a significantly higher density in the southern sections compared to the north. It demonstrates a strong positive spatial autocorrelation. (2) In seven distinct categories of hydronyms, “Administrative and Regional Names” predominate (38.6%), reflecting the canal’s profound function in political governance, while the prevalence of “Composite Names” (21.4%) illustrates the complex adaptation between human society and the hydrological environment. (3) Hydronyms exhibit a significant clustered pattern with a distinct north–south divergence near the 34°N latitude, reflecting a dual cultural structure. (4) Contrary to the view that urbanisation erodes culture, our GWR results identify that urbanisation and economic Level exert the most decisive positive influence on hydronym retention. In light of these findings, this study proposes a theoretical framework for digital heritage conservation and offers spatial-specific strategies for the sustainable development and communication of the Grand Canal.
Huang et al. (Thu,) studied this question.