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

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