Data underlying the publication: Applying transfer function-noise modelling to characterize soil moisture dynamics: a data-driven approach using remote sensing data
Datacite citation style:
Michiel Pezij; D.C.M. (Denie) Augustijn; Hendriks, D.M.D. (Dimmie); Hulscher, S.J.M.H. (Suzanne) (2019): Data underlying the publication: Applying transfer function-noise modelling to characterize soil moisture dynamics: a data-driven approach using remote sensing data. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/uuid:ba33fc56-e07b-4547-9630-9b1565d18040
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
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.
history
- 2019-10-28 first online, published, posted
publisher
4TU.Centre for Research Data
format
media types: application/vnd.google-earth.kml+xml, application/zip, text/csv, text/plain, text/x-python
funding
- NWO-TTW, 13871
organizations
University of Twente, Faculty of Engineering Technology, Department of Water Engineering & Management
DATA
files
- 591 bytes md5 Twente (region).kml
- 735,575 bytes md5 data.zip
- download all files (zip)