[HTML][HTML] Data-driven modelling of hydraulic-head time series: results and lessons learned from the 2022 Groundwater Time Series Modelling Challenge

RA Collenteur, E Haaf, M Bakker… - Hydrology and Earth …, 2024 - hess.copernicus.org
This paper presents the results of the 2022 Groundwater Time Series Modelling Challenge,
where 15 teams from different institutes applied various data-driven models to simulate …

Machine Learning-Based Reconstruction and Prediction of Groundwater Time Series in the Allertal, Germany.

TV Tran, A Peche, R Kringel, K Brömme… - Water …, 2025 - search.ebscohost.com
State-of-the-art hydrogeological investigations use transient calibrated numerical flow and
transport models for multiple scenario analyses. However, the transient calibration of …

Data-driven modeling of hydraulic head time series: results and lessons learned from the 2022 groundwater modeling challenge

RA Collenteur, E Haaf, M Bakker… - Hydrology and Earth …, 2024 - hess.copernicus.org
This paper presents the results of the 2022 groundwater time series modeling challenge,
where 15 teams from different institutes applied various data-driven models to simulate …

Zum Einsatz von Maschinellem Lernen in der Umweltverwaltung: Der Simplex4Learning Ansatz

A Abecker, M Budde, F Fuchs-Kittowski, J Großmann… - INFORMATIK 2024, 2024 - dl.gi.de
Ziel des im Herbst 2023 gestarteten Forschungsvorhabens Simplex4Learning ist es, die
großen und heterogenen Datenbestände der Umweltbehörden für intelligente Analysen mit …

Data-driven modelling of hydraulic-head time series

RA Collenteur, E Haaf, M Bakker, T Liesch, A Wunsch… - 2024 - repository.tudelft.nl
This paper presents the results of the 2022 Groundwater Time Series Modelling Challenge,
where 15 teams from different institutes applied various data-driven models to simulate …