All water research trends
Steady theme

lstm nse

One of 50 themes found in 20,416 EGU water abstracts (2024 to 2026). Its most distinctive words are below — they are what separates this body of work from the rest of the corpus.

lstmnsepost-processingxgboostannungauged
416
abstracts in this theme
2.0% of the water corpus · 24 of 50 by size
73.8%
use machine learning
60.6 points above the 13.2% corpus average
+0.05
points of share, 2024 to 2026
21 of 50 by trend
#4
of 50 for AI penetration
among the most AI-heavy themes

How to read this theme

This theme holds 416 of the 20,416 water abstracts, making it the 24th-largest of the 50 themes. Between 2024 and 2026 its share barely moved, by 0.05 points.

73.8% of its abstracts were flagged as using machine learning, 60.6 points above the 13.2% corpus average. AI is already the dominant method here, so novelty is more likely to come from the science than from the model.

Find data for this theme

Search the directory for datasets matching this theme's defining terms.

Semantically nearest themes

Themes that sit closest to this one on the semantic map — the work that reads most like it.

Themes are clusters found by grouping abstracts on their sentence embeddings, so their boundaries are statistical rather than official EGU categories. "Uses AI" comes from a keyword detector validated at precision 0.95 and recall 0.9. Point estimates carry roughly half a point to a point of uncertainty from the clustering. Full method on the main trends page.