• Øster Voldgade 10
    1350 Copenhagen K
    Denmark

Beregnet ud fra antal publikationer lagret i Pure og citationer fra Scopus
20142022

Publikationer pr. år

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Personlig profil

CV

Education

PhD: Geology, University of Copenhagen, Faculty of Science. Obtained November 2016.

MSc: Geography and Geoinformatics, University of Copenhagen, Faculty of Science. Obtained June 2013.

BSc: Geography (major in physical geography, minor in computer science), LMU Munich. Obtained June 2010.

Academic Positions

Year

Organisation

Position

2021 - date

Geological Survey of Denmark and Greenland (GEUS)

Senior Researcher, Department of Hydrology

2017 - 2021

GEUS

Researcher, Department of Hydrology

2016 - 2017

GEUS

Postdoc, Department of Hydrology

2013 - 2016

University of Copenhagen

PhD Student, Department of Geoscience and Natural Resource Management

Research Profile

I am an expert in hydrological modelling and I apply hydrological models to study the impact of climate change and water resources management on the hydrological system. My research focus lies on the integration of satellite remote sensing data into the model building. Further, I peruse research on environmental big data for the advancement of machine learning in hydrology. I have pioneered the development of machine learning models for subsurface redox conditions, rainfall-runoff modelling and groundwater levels. Recently, my research targets the relevance of groundwater in the context of emissions of greenhouse gases from peatlands. I have successfully attracted funding as PI and Co-PI from a variety of Danish funding agencies and have experience in project management and student supervision.

Selected Current Projects

  • Revision of greenhouse gas emission inventory for peatland soils in Denmark. I develop a high-resolution machine learning model predicting groundwater levels for lowland soils across Denmark. The project is funded by the Danish Ministry of Climate, Energy and Utilities.
  • Development and updating of the redox map of Denmark using machine learning. As PI, I am responsible for project management and implementing the machine learning model. The project is funded by the Danish Environmental Protection Agency.
  • Irrigation water use quantification from space using satellites. The project applies a combination of satellite remote sensing models and hydrological models to estimate water use of irrigation agriculture. As Co-PI, I am responsible for the supervision of a PhD student as well as for project management. The project is funded by the Independent Research Fund Denmark.
  • Building Climate Resilience into Basin Water Management. The project addresses climate change impacts on the water resources for two river basins in Ghana. I apply machine learning to model land use / land cover changes in West Africa based on satellite remote sensing data and supervises a PhD student. The project is funded by the DANIDA Fellowship Centre on behalf of the Ministry of Foreign Affairs.
  • Strategic sector cooperation between Denmark and India. The project initiates the cooperation between India and Denmark on water-related issues. In this context, I conduct hydrological modelling and quantify irrigation using remote sensing data. The project is funded by the the Danish Environmental Protection Agency.

Student Supervision

  • BSc level: 1 completed (Technical University of Denmark)
  • MSc level: 1 current (University of Copenhagen), 1 completed (Technical University of Denmark).
  • PhD level: 2 current (University of Copenhagen and Kwame Nkrumah University of Science and Technology).

 

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