Vega, Jorge (2020): SMAP and Sentinel-1 data of the Rhine basin. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/uuid:99176da8-4ca5-4617-aacd-c801df4a8214

Usage statistics

Categories

• Land and Water Management
• Soil Sciences
• Physical Geography and Environmental Geoscience

Keywords

Data assimilation master thesis soil moisture Soil Moisture Active Passive (SMAP) Water Content

Geolocation

view on openstreetmap

Time coverage

2015/2018

Licence

CC0

Export as...

RefWorks BibTeX Reference Manager Endnote DataCite NLM DC CFF

by Jorge Vega

SMAP L3, corresponds to high-resolution satellite soil moisture in (m3 m-3) from active and passive sensors. This dataset can be useful to perform data assimilation of soil moisture with Delft-FEWS system for hydrologic forecasting of the Rhine basin. This will improve the accuracy of the discharge predictions because of the improvements on the states of soil moisture. The Sentinel-1 dataset corresponds to high-resolution soil moisture (%) from a passive sensor. This dataset can be used for data assimilation too, but the improvements are not as good as SMAP.

History

• 2020-07-09 first online, published, posted

Publisher

4TU.ResearchData

Format

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

Organizations

Wageningen University & Research

Contributors

• Weerts, A.H. (Albrecht)