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Data underlying the publication: Applying transfer function-noise modelling to characterize soil moisture dynamics: a data-driven approach using remote sensing data

dataset
posted on 28.10.2019 by Michiel Pezij, D.C.M. (Denie) Augustijn, D.M.D. (Dimmie) Hendriks, S.J.M.H. (Suzanne) Hulscher
This dataset includes the input data, Python scripts, and Pastas model output for the scientific manuscript "Applying transfer function-noise modelling to characterize soil moisture dynamics: a data-driven approach using remote sensing data". The manuscript is currently under review. The data covers the years 2016, 2017, and 2018. We refer to the readme file included in the dataset for further details.

Funding

NWO-TTW, 13871

History

Contributors

University of Twente, Faculty of Engineering Technology, Department of Water Engineering & Management

Publisher

4TU.Centre for Research Data

Time coverage

2016/2018

Geolocation

Twente (region)

Geolocation Longitude

6.688

Geolocation Latitude

52.304

Format

media types: application/vnd.google-earth.kml+xml, application/zip, text/csv, text/plain, text/x-python

Licence

Exports