Building knowledge to optimise the management and protection of Danish water resources and the public’s drinking water supply as well as the impact of groundwater on Danish nature and the environment. Programme areas include mapping, establishing and managing monitoring programmes, understanding the water cycle and water quality.

The Water resources programme includes contributions from the following departments at GEUS:
  • Groundwater and Quaternary Geology Mapping
  • Geochemistry
  • Hydrology

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31 to 36 of 36 Results
DK-model2019(Geus.dk)
Aug 25, 2022
This folder contain both GIS data with simulation results, calibrationstatistics and model set up data from The National Hydrological Model, version 2019 (DK-model2019) and the acctual modelset up in MIKESHE/MikeHYDRO. The hydrogeological layers in DKmodel2019 are also available...
Water table depth for Danish lowland soils
Jun 14, 2022
Koch, Julian, 2022, "Water table depth for Danish lowland soils", https://doi.org/10.22008/FK2/0AFGQT, GEUS Dataverse, V1
The map depicts a long-term average water table depth in Danish lowland soils at 10 m spatial resolution. The long-term average represents summer conditions for a time period from 2000 to 2020. The map has been generated using a gradient boosting with decision tree algorithm, sim...
Redoxmaps from CRES2016
Jan 10, 2022
Seidenfaden, Ida Karlsson, 2022, "Redoxmaps from CRES2016", https://doi.org/10.22008/FK2/YEMDIS, GEUS Dataverse, V1
Resulting redoxmaps from the paper https://doi.org/10.5194/hess-2020-570. Maps are given for 45 combinations of 4 land use scenarioes, observational land use and climate data, and four different future climate models. Please see publication for details.
Catchment Dataset Denmark
Dec 7, 2021
Koch, Julian, 2021, "Catchment Dataset Denmark", https://doi.org/10.22008/FK2/YCQXTR, GEUS Dataverse, V1
This dataset can be used as input data for rainfall-runoff modelling for over 300 Danish catchments. Specifically, this dataset was used for a machine learning (LSTM) model application using the neuralhydrology codebase: https://neuralhydrology.github.io/ The data provided allows...
Metamodel transferability dataset
Aug 6, 2021
Bjerre, Elisa, 2021, "Metamodel transferability dataset", https://doi.org/10.22008/FK2/QS5PSL, GEUS Dataverse, V1
The dataset contains all input covariates and target variable for the random forest model presented in the manuscript "A Random Forest Metamodel for Predicting Drainage Fraction and Assessment of Model Transferability to New Spatial Domains" submitted to Water Resources Research
Gridded European Evapotranspiration Climatologies
Gridded European Evapotranspiration Climatologies
Jun 21, 2021
Stisen, Simon; Soltani, Mohsen; Mendiguren, Gorka; Langkilde, Henrik; Garcia, Monica; Koch, Julian, 2021, "Gridded European Evapotranspiration Climatologies", https://doi.org/10.22008/FK2/T6NBHH, GEUS Dataverse, V1
Spatial patterns in long-term evapotranspiration (ET) represent a unique source of information for evaluating the spatial pattern performance of distributed hydrological models at river basin to continental scale. This kind of model evaluation is getting increased attention, ackn...
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