Assimilation of Backscatter Observations into a Hydrological Model: A Case Study in Belgium Using ASCAT Data

We investigated the possibilities of improving hydrological simulations by assimilating radar backscatter observations from the advanced scatterometer (ASCAT) in the hydrological model SCHEME using a calibrated water cloud model (WCM) as an observation operator. The WCM simulates backscatter based on soil moisture and vegetation data and can therefore be used to generate observation predictions for data assimilation. The study was conducted over two Belgian catchments with different hydrological regimes: the Demer and the Ourthe catchment. The main differences between the two catchments can be... Mehr ...

Verfasser: Pierre Baguis
Alberto Carrassi
Emmanuel Roulin
Stéphane Vannitsem
Sara Modanesi
Hans Lievens
Michel Bechtold
Gabrielle De Lannoy
Dokumenttyp: Artikel
Erscheinungsdatum: 2022
Reihe/Periodikum: Remote Sensing, Vol 14, Iss 5740, p 5740 (2022)
Verlag/Hrsg.: MDPI AG
Schlagwörter: hydrological model / water cloud model / data assimilation / backscatter / leaf area index / soil moisture / Science / Q
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-28972553
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : https://doi.org/10.3390/rs14225740

We investigated the possibilities of improving hydrological simulations by assimilating radar backscatter observations from the advanced scatterometer (ASCAT) in the hydrological model SCHEME using a calibrated water cloud model (WCM) as an observation operator. The WCM simulates backscatter based on soil moisture and vegetation data and can therefore be used to generate observation predictions for data assimilation. The study was conducted over two Belgian catchments with different hydrological regimes: the Demer and the Ourthe catchment. The main differences between the two catchments can be summarized in precipitation and streamflow levels, which are higher in the Ourthe. The data assimilation method adopted here was the ensemble Kalman filter (EnKF), whereby the uncertainty of the state estimate was described via the ensemble statistics. The focus was on the optimization of the EnKF, and possible solutions to address biases introduced by ensemble perturbations were investigated. The latter issue contributes to the fact that backscatter data assimilation only marginally improves the overall scores of the discharge simulations over the deterministic reference run, and only for the Ourthe catchment. These performances, however, considerably depend on the period considered within the 5 years of analysis. Future lines of research on bias correction, the data assimilation of soil moisture and backscatter data are also outlined.