Journal Article

FZJ-2019-01344

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Iterative filter based estimation of fully 3D heterogeneous fields of permeability and Mualem-van Genuchten parameters

Chaudhuri, A. (Corresponding author) ; Hendricks-Franssen, H.-J.FZJ* ; Sekhar, M.

2018
Elsevier Science Amsterdam [u.a.]

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Please use a persistent id in citations: doi:10.1016/j.advwatres.2018.10.023

Abstract: The accurate modeling of flow and transport in the vadose zone for agricultural and environmental applications requires knowledge about soil parameters. Soil parameters vary in space depending on soil texture and structure. In the present synthetic study we considered spatial variation of permeability (k), inverse of capillary entry pressure head (αVG) and exponent (n) of the Mualem-van Genuchten model. The iterative Ensemble Kalman filter (IEnKF) can estimate the spatially variable soil parameters if measurements of water saturation at different locations and times are available. We used as input daily precipitation data from the Berambadi catchment (southern India). We first considered that the parameters vary horizontally but are constant in the vertical direction. In this case log (k) and log (αVG) can be estimated satisfactorily with 30%–40% reduction of RMSE (compared to open loop runs), if the initial guess of the spatial correlation lengths of the heterogeneous fields is equal to or larger than the unknown, true values. The estimation of exponent n is poorer as the reduction of RMSE is just 20%. If vertical heterogeneity of the parameters is considered the estimation of log (k) and log (αVG) is only improved for the upper 1.5 m and estimation of n is not improved. We also demonstrate that the estimation problem can be simplified when flow in the unsaturated zone is predominantly vertical. If in this case soil hydraulic parameters are estimated with IEnKF at measurement locations and afterwards interpolated with kriging, results are produced with a similar quality as with 3D-IEnKF.

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Contributing Institute(s):

1. Agrosphäre (IBG-3)

Research Program(s):

1. 255 - Terrestrial Systems: From Observation to Prediction (POF3-255) (POF3-255)

Appears in the scientific report 2019

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Database coverage:
; Clarivate Analytics Master Journal List ; Current Contents - Engineering, Computing and Technology ; Ebsco Academic Search ; IF < 5 ; JCR ; Nationallizenz ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Web of Science Core Collection

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