Water resources

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

Explore our research group and project dataverses and datasets below.

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551 to 558 of 558 Results

DK_cv1_seed5.yml Jun 2, 2022 - Catchment Dataset Denmark Plain Text - 9.3 KB - MD5: 530d8eff64573460d5c87008c0c67e33
DK_cv1_test.txt Jun 2, 2022 - Catchment Dataset Denmark Plain Text - 479 B - MD5: 1ba9192f7754bb0a93b6d61e4034e2f5
DK_cv1_train.txt Jun 2, 2022 - Catchment Dataset Denmark Plain Text - 1.9 KB - MD5: 48b863094a7a30e92969dbec79ca2198
readme.docx Jun 2, 2022 - Catchment Dataset Denmark Unknown - 30.3 KB - MD5: fff0aba8e3fb971ebef709293573ff1f
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 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...

DK_cv1_seed5.yml

Jun 2, 2022 - Catchment Dataset Denmark

Plain Text - 9.3 KB -

DK_cv1_test.txt

Jun 2, 2022 - Catchment Dataset Denmark

Plain Text - 479 B -

DK_cv1_train.txt

Jun 2, 2022 - Catchment Dataset Denmark

Plain Text - 1.9 KB -

readme.docx

Jun 2, 2022 - Catchment Dataset Denmark

Unknown - 30.3 KB -

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

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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