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Erschienen in:
2020 | OriginalPaper | Buchkapitel
8. Unsupervised Constraint for Hydrologic Data Assimilation
verfasst von : Mehdi Khaki
Erschienen in: Satellite Remote Sensing in Hydrological Data Assimilation
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Abstract
The standard ensemble data assimilation schemes often violate the dynamical balances of hydrological models, on their estimates, in particular, the fundamental water balance equation, which relates water storage and water flux changes. The present study aims at extending the recently introduced Weak Constrained Ensemble Kalman Filter (WCEnKF) to a more general framework, namely unsupervised WCEnKF (UWCEnKF), in which the covariance of the water balance model is no longer known, thus requiring its estimation along with the model state variables. This extension is introduced because WCEnKF was found to be strongly sensitive to the (manual) choice of this covariance.