MATLAB algorithm to implement soil water data assimilation with the Ensemble Kalman Filter using HYDRUS

Javier Valdes-Abellan; Yakov Pachepsky; Gonzalo Martinez

doi:10.1016/j.mex.2018.02.008

MATLAB algorithm to implement soil water data assimilation with the Ensemble Kalman Filter using HYDRUS

MethodsX. 2018 Mar 7:5:184-203. doi: 10.1016/j.mex.2018.02.008. eCollection 2018.

Authors

Javier Valdes-Abellan¹, Yakov Pachepsky², Gonzalo Martinez³

Affiliations

¹ Department of Civil Engineering, University of Alicante, Alicante, Spain.
² USDA-ARS, Environmental Microbial and Food Safety Lab., Beltsville, MD, USA.
³ Department of Applied Physics, University of Córdoba, Córdoba, Spain.

Abstract

Data assimilation is becoming a promising technique in hydrologic modelling to update not only model states but also to infer model parameters, specifically to infer soil hydraulic properties in Richard-equation-based soil water models. The Ensemble Kalman Filter method is one of the most widely employed method among the different data assimilation alternatives. In this study the complete Matlab© code used to study soil data assimilation efficiency under different soil and climatic conditions is shown. The code shows the method how data assimilation through EnKF was implemented. Richards equation was solved by the used of Hydrus-1D software which was run from Matlab. •MATLAB routines are released to be used/modified without restrictions for other researchers•Data assimilation Ensemble Kalman Filter method code.•Soil water Richard equation flow solved by Hydrus-1D.

Keywords: Climate/soil EnKF efficiency; EnKF; Hydrus; Soil water flux modelling.