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GEMS-GER: a machine learning benchmark dataset of long-term groundwater levels in Germany with meteorological forcings and site-specific environmental features

<p>We present GEMS-GER (Groundwater Levels, Environment, Meteorology, Site Properties), the first benchmark dataset specifically designed for machine learning applications in long-term groundwater level modeling in Germany. The dataset comprises 32 years of gapless weekly observations from 3207 moni...

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Principais autores: M. Ohmer, T. Liesch, B. Habbel, B. Heudorfer, M. Gomez, P. Clos, M. Nölscher, S. Broda
Format: Artigo
Jezik:Inglês
Izdano: Copernicus Publications 2026-01-01
Serija:Earth System Science Data
Online dostop:https://essd.copernicus.org/articles/18/77/2026/essd-18-77-2026.pdf
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