Ensemble Kalman Inversion for upstream parameter estimation and indirect streamflow correction: A simulation study

Andrew Pensoneault; Witold F. Krajewski; Nicolás Velásquez; Xueyu Zhu; Ricardo Mantilla

doi:10.1016/j.advwatres.2023.104545

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Ensemble Kalman Inversion for upstream parameter estimation and indirect streamflow correction: A simulation study

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Ensemble Kalman Inversion for upstream parameter estimation and indirect streamflow correction: A simulation study

Andrew Pensoneault, Witold F. Krajewski, Nicolás Velásquez, Xueyu Zhu and Ricardo Mantilla

Advances in water resources, Vol.181, 104545

11/2023

DOI: 10.1016/j.advwatres.2023.104545

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Abstract

Data assimilation (DA) techniques such as the Ensemble Kalman filter (EnKF) and its extensions allow for real-time corrections of state-space models and model parameters based on an assumption of Gaussian error. The hydrological DA literature primarily documents applications of the EnKF to solve sequential state estimation problems. Recent advances in the DA literature demonstrate the potential of applying EnKF-based methods as efficient, derivative-free algorithms to solve various general Bayesian inverse problems, such as parameter estimation, while simultaneously providing Uncertainty Quantification (UQ). In this paper, the authors employ the Ensemble Kalman Inversion (EKI) algorithm to infer the distribution of a set of routing parameters. Through this correction, we improve streamflow at locations upstream of the gauged site in a virtual catchment setting. The algorithm enables learning spatially distributed routing parameters with observations available only at the outlet. The study reveals that this method sufficiently improves model performance throughout the basin. The performance of this method is demonstrated in a virtual catchment for three different model/data configurations. Favorable results, even with model misspecification, indicate that this method holds promise for operational application and more general hydrologic parameter estimation problems.

Details

Title: Subtitle: Ensemble Kalman Inversion for upstream parameter estimation and indirect streamflow correction: A simulation study
Creators: Andrew Pensoneault - University of Iowa
Witold F. Krajewski - University of Iowa
Nicolás Velásquez - University of Iowa
Xueyu Zhu - University of Iowa
Ricardo Mantilla - University of Manitoba
Resource Type: Journal article
Publication Details: Advances in water resources, Vol.181, 104545
DOI: 10.1016/j.advwatres.2023.104545
ISSN: 0309-1708
eISSN: 1872-9657
Language: English
Electronic publication date: 10/2023
Date published: 11/2023
Academic Unit: Civil and Environmental Engineering; IIHR--Hydroscience and Engineering; Mathematics
Record Identifier: 9984476554602771

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