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

    Dataset

    Description

    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.

    Data-driven modelling, Hydrology, Remote sensing, Soil moisture, Transfer function-noise modelling, Unsaturated zone, Water management, Environmental science and management, Land and water management
    Date made available28 Oct 2019
    Publisher4TU.Centre for Research Data
    Date of data production2016 - 2018
    Geographical coverageTwente (region)
    Geospatial point52.279973, 6.725305

    Cite this

    Pezij, M. (Creator), Augustijn, D. C. M. (Creator), Hendriks, D. M. D. (Creator), Hulscher, S. J. M. H. (Creator) (28 Oct 2019). Data underlying the publication: Applying transfer function-noise modelling to characterize soil moisture dynamics: a data-driven approach using remote sensing data. 4TU.Centre for Research Data. 10.4121/uuid:ba33fc56-e07b-4547-9630-9b1565d18040