Evaluation of the soil moisture model with data assimilation by the triple collocation method

Olena Kozhushko; Mykhailo Boiko; Mykola Kovbasa; Petro Martyniuk; Olha Stepanchenko; Mykola Uvarov

doi:10.31713/MCIT.2020.11

Authors

Olena Kozhushko NUWEE https://orcid.org/0000-0001-9934-1013 (unauthenticated)
Mykhailo Boiko National University of Water and Environmental Engineering , National University of Water and Environmental Engineering https://orcid.org/0000-0002-0962-8625 (unauthenticated)
Mykola Kovbasa EOS Data Analytics, V.Ye. Lashkaryov Institute of Semiconductor Physics of the NAS of Ukraine https://orcid.org/0000-0001-7988-0175 (unauthenticated)
Petro Martyniuk National University of Water and Environmental Engineering , National University of Water and Environmental Engineering https://orcid.org/0000-0002-2750-2508 (unauthenticated)
Olha Stepanchenko National University of Water and Environmental Engineering , National University of Water and Environmental Engineering https://orcid.org/0000-0001-6033-7404 (unauthenticated)
Mykola Uvarov EOS Data Analytics, G. V. Kurdyumov Institute for Metal Physics https://orcid.org/0000-0002-0966-7683 (unauthenticated)

DOI:

https://doi.org/10.31713/MCIT.2020.11

Keywords:

data assimilation, Newtonian nudging, mathematical modelling, soil moisture, triple collocation

Abstract

This paper deals with a nonlinear soil moisture transport problem, solved with addition of satellite observed soil moisture. The satellite data are assimilated into the model using Newtonian nudging method. Evaluation is done by the triple collocation method, which involves three independent data sources: model results, ground stations and ERA5 climatic data. The results testify that model results are nearly as accurate as the ground station measurements.

Evaluation of the soil moisture model with data assimilation by the triple collocation method

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