Published April 18, 2023
| Version v1
Dataset
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Dealing with Sub-pixel Landscape Elements in Distributed Rainfall-Runoff Modelling in Agricultural Catchments
Description
The Input_Data.zip file contains the processed data used as input data for the research paper "Dealing with Sub-pixel Landscape Elements in Distributed Rainfall-Runoff Modelling in Agricultural Catchments".
- The Digital Elevation Models (DEMs) are adapted from the 5 m resolution "DEM DHMV II" (available from https://download.vlaanderen.be/Producten/Detail/938). The scaling factors used to calculate per-pixel values of upscaled hydro-physical parameters are derived from the digital elevation model.
- The raster files representing the Manning's roughness coefficient in the watershed for 2006, 2007, 2013, 2016 and 2019 are based on landcover datasets created by combining the Flemish agricultural parcel dataset for each year (available from https://www.vlaanderen.be/datavindplaats/catalogus/landbouwgebruikspercelen-lv-2021) with the road network dataset (available from https://www.vlaanderen.be/digitaal-vlaanderen/onze-oplossingen/basiskaart-vlaanderen-grb) and digitised polygons of forested areas based on areal images (https://www.vlaanderen.be/datavindplaats/catalogus/orthofotomozaiek-grootschalig-winteropnamen-kleur-2013-2015-vlaanderen).
- The vegetated landscape element (vLE) configurations were created based on agricultural parcel boundaries (available from https://www.vlaanderen.be/datavindplaats/catalogus/landbouwgebruikspercelen-lv-2021) and rasterising them.
- Rainfall intensity measurements were extracted from waterinfo.be for the station with name "Niel-bij-St.-Truiden_P", number "01P09_012", and coordinates (LAT/LON) "50.7378581908062/5.14225742349451".
- Discharge measurements were extracted from waterinfo.be for the discharge station with name "Gingelom/Heulegracht" and number "LS09_15F".
The scripts.zip file contains the scripts used to process the data.
The Output.zip file contains the output files created by the scripts while making use of the Python-based Landlab model environment (https://landlab.github.io/#/)
This research was funded by Fonds Wetenschappelijk Onderzoek (FWO), grant number 1SB6821N.