  In the new global era, determining trends can play an important role in
guiding researchers, scientists, and agencies. The main faced challenge is to
track the emerging topics among the stacked publications. Therefore, any study
done to propose the trend topics in a field to foresee upcoming subjects is
crucial. In the current study, the trend topics in the field of "Hydrology"
have been attempted to evaluate. To do so, the model is composed of three key
components: a gathering of data, preprocessing of the article's significant
features, and determining trend topics. Various topic models including Latent
Dirichlet Allocation (LDA), Non-negative Matrix Factorization (NMF), and Latent
Semantic Analysis (LSA) have been implemented. Comparing the obtained results
with respect to the $C_V$ coherence score, in 2022, the topics of "Climate
change", "River basin", "Water management", "Natural hazards/erosion", and
"Hydrologic cycle" have been obtained. According to a further analysis, it is
shown that these topics keep their impact on the field in 2023, as well.
