EnKF with closed-eye period - towards a consistent aggregation of information in soil hydrology

The representation of soil water movement exposes uncertainties in all model components. We assess the key uncertainties for the specific hydraulic situation of a 1-D soil profile with TDR (time domain reflectometry)-measured water contents. The uncertainties addressed are initial condition, soil hydra...

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Bibliographic Details
Main Authors: Bauser, Hannes (Author) , Jaumann, Stefan (Author) , Berg, Daniel (Author) , Roth, Kurt (Author)
Format: Article (Journal)
Language:English
Published: 19 December 2016
In: Hydrology and earth system sciences
Year: 2016, Volume: 20, Issue: 12, Pages: 4999-5014
ISSN:1607-7938
DOI:10.5194/hess-20-4999-2016
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.5194/hess-20-4999-2016
Verlag, lizenzpflichtig, Volltext: https://www.hydrol-earth-syst-sci.net/20/4999/2016/
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Author Notes:Hannes H. Bauser, Stefan Jaumann, Daniel Berg, and Kurt Roth
Description
Summary:The representation of soil water movement exposes uncertainties in all model components. We assess the key uncertainties for the specific hydraulic situation of a 1-D soil profile with TDR (time domain reflectometry)-measured water contents. The uncertainties addressed are initial condition, soil hydraulic parameters, small-scale heterogeneity, upper boundary condition, and the local equilibrium assumption by the Richards equation. We employ an ensemble Kalman filter (EnKF) with an augmented state to represent and estimate all key uncertainties, except for the intermittent violation of the local equilibrium assumption. For the latter, we introduce a closed-eye EnKF to bridge the gap. Due to an iterative approach, the EnKF was capable of estimating soil parameters, Miller scaling factors and upper boundary condition based on TDR measurements during a single rain event. The introduced closed-eye period ensured constant parameters, suggesting that they resemble the believed true material properties. This closed-eye period improves predictions during periods when the local equilibrium assumption is met, but requires a description of the dynamics during local nonequilibrium phases to be able to predict them. Such a description remains an open challenge. Finally, for the given representation our results show the necessity of including smallscale heterogeneity. A simplified representation with Miller scaling already yielded a satisfactory description.
Item Description:Gesehen am 04.05.2020
Physical Description:Online Resource
ISSN:1607-7938
DOI:10.5194/hess-20-4999-2016