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 40 of 40 Results
Jan 10, 2023
Højberg, Anker; Thodsen, Hans; Børgense, Christen Duus, 2023, "Nitrate Retentionmap DK", https://doi.org/10.22008/FK2/JLINZY, GEUS Dataverse, V1
Map showing the degree of nitrate retention in the subsurface and surface waters before they reach the coast calculated as an average for the period 1990-2010. Development and production of the map was carried out in cooperation between GEUS and the Univerity of Aarhus during 201...
Nov 30, 2022
Madsen, Rasmus Bødker, 2022, "Realizations of the subsurface representing interpretation uncertainty of a hydrostratigraphic model from Egebjerg, Denmark", https://doi.org/10.22008/FK2/CHXSAK, GEUS Dataverse, V1
Ensemble of 200 realizations of the subsurface near Egebjerg Denmark. The realizations were made using the GDM method (https://doi.org/10.1016/j.enggeo.2022.106833) to demonstrate the method. The realizations represent the interpretation uncertainty of the layer boundaries from a...
Aug 25, 2022 - DK-model2019
Ondracek, Maria, 2022, "DK-model2019 - Model data, calibration statistics and simulation results (GIS)", https://doi.org/10.22008/FK2/I2S92O, GEUS Dataverse, V1
This folder contains model data, calibration statistics and simulation results from DK-model2019. Grid files and .shp files are assembled in ArcGIS Pro v.3.0.1. Modeldata contains hydrological and geological data from DK-model2019. DK-model2019 setup and calibration is described...
Aug 25, 2022 - DK-model2019
Ondracek, Maria, 2022, "DK-model2019 - Model data (GIS)", https://doi.org/10.22008/FK2/DIXM34, GEUS Dataverse, V1
This folder contains the hydrological and geological data from DK-model2019. Grid files and .shp files are assembled in ArcGIS Pro v.3.0.1. DK-model2019 setup and calibration is described in GEUS report 2019/31.
Aug 25, 2022 - DK-model2019
Ondracek, Maria, 2022, "DK-model2019 - Calibration statistics (GIS)", https://doi.org/10.22008/FK2/0JRWGS, GEUS Dataverse, V1
This folder contains the calibrationstatistics from DK-model2019. Grid files and .shp files are assembled in ArcGIS Pro v.3.0.1. DKmodel2019 setup and calibration is described in GEUS report 2019/31.
Aug 25, 2022 - DK-model2019
Ondracek, Maria, 2022, "DK-model2019 - Simulation results (GIS)", https://doi.org/10.22008/FK2/P88XCU, GEUS Dataverse, V1
This folder contains contain various results simulated with DK-model2019. Grid files and .shp files are assembled in ArcGIS Pro v.3.0.1. For results regarding streamflow, seepage from groundwater to streams, depth to groundwater table, net precipitation, recharge and water veloci...
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.
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...
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
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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