Articles | Volume 23, issue 2
Hydrol. Earth Syst. Sci., 23, 1163–1178, 2019
https://doi.org/10.5194/hess-23-1163-2019
Hydrol. Earth Syst. Sci., 23, 1163–1178, 2019
https://doi.org/10.5194/hess-23-1163-2019

Research article 28 Feb 2019

Research article | 28 Feb 2019

Covariance resampling for particle filter – state and parameter estimation for soil hydrology

Daniel Berg et al.

Data sets

Covariance resampling for particle filter -- state and parameter estimation for soil hydrology [dataset] D. Berg, H. H. Bauser, and K. Roth https://doi.org/10.11588/data/MFU6EV

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Short summary
Particle filters are becoming popular for state and parameter estimations in hydrology. The renewal of the ensemble (resampling) is crucial in preventing filter degeneration. We introduce a resampling method that uses the weighted covariance of the ensemble, which contains information between observed and unobserved dimensions, to generate new ensemble members. This allows us to estimate the state and parameters for a rough initial guess in a synthetic hydrological case with just 100 particles.