Soil Moisture Data Assimilation in a Hydrological Model: A Case Study in Belgium Using Large-Scale Satellite Data
In the present study, we focus on the assimilation of satellite observations for Surface Soil Moisture (SSM) in a hydrological model. The satellite data are produced in the framework of the EUMETSAT project H-SAF and are based on measurements with the Advanced radar Scatterometer (ASCAT), embarked on the Meteorological Operational satellites (MetOp). The product generated with these measurements has a horizontal resolution of 25 km and represents the upper few centimeters of soil. Our approach is based on the Ensemble Kalman Filter technique (EnKF), where observation and model uncertainties ar... Mehr ...
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Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2017 |
Reihe/Periodikum: | Remote Sensing, Vol 9, Iss 8, p 820 (2017) |
Verlag/Hrsg.: |
MDPI AG
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Schlagwörter: | data assimilation / ensemble Kalman filter / satellite data / remote sensing / soil moisture / hydrological model / Science / Q |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-27391048 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://doi.org/10.3390/rs9080820 |