Simon Stisen

Professor

Geological Survey of Denmark and Greenland

Denmark

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Simon Stisen is a Professor at the Geological Survey of Denmark and Greenland in Copenhagen, Denmark. His research primarily focuses on hydrometeorology, hydrological modeling, and the quantification of irrigation through innovative methods, including machine learning and satellite data analysis. Recent publications highlight his work on streamflow estimation, greenhouse gas emissions in peatlands, and the dynamics of forest canopy interception loss. He is committed to enhancing hydrological process understanding and developing credible models for effective water management and climate adaptation.

Simon Stisen

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Articles (15)

CAMELS-DK: hydrometeorological time series and landscape attributes for 3330 Danish catchments with streamflow observations from 304 gauged stations

Tradeoffs Between Temporal and Spatial Pattern Calibration and Their Impacts on Robustness and Transferability of Hydrologic Model Parameters to Ungauged Basins

A national-scale hybrid model for enhanced streamflow estimation – consolidating a physically based hydrological model with long short-term memory (LSTM) networks

An inter-comparison of approaches and frameworks to quantify irrigation from satellite data

The precision of satellite-based net irrigation quantification in the Indus and Ganges basins

Water-table-driven greenhouse gas emission estimates guide peatland restoration at national scale

Seasonal dynamics of canopy interception loss within a deciduous and a coniferous forest

Towards more credible models in catchment hydrology to enhance hydrological process understanding: Preface

A New Digital Twin for Climate Change Adaptation, Water Management, and Disaster Risk Reduction (HIP Digital Twin)

Machine-learning-based downscaling of modelled climate change impacts on groundwater table depth

Exploring the combined use of SMAP and Sentinel-1 data for downscaling soil moisture beyond the 1 km scale

Spatial pattern‐based performance evaluation and uncertainty analysis of a distributed hydrological model

Climate Normalized Spatial Patterns of Evapotranspiration Enhance the Calibration of a Hydrological Model

Hunting for Information in Streamflow Signatures to Improve Modelled Drainage

Hydrological process knowledge in catchment modelling – Lessons and perspectives from 60 years development

Collaborators (9)

Jesper Christiansen

Luis Eduardo Samaniego Eguiguren

Mie Andreasen

Rasmus Fensholt

Jens Christian Refsgaard

Cecilie Hermansen

lars troldborg

Majken Looms

Rena Meyer

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