[1745] - Comparison of different assimilation methodologies of groundwater levels to improve predictions of root zone soil moisture with an integrated terrestrial system model

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Citation
Zhang, H., Kurtz, W., Kollet, S., Vereecken, H., Hendricks-Franssen, H., 2018. Comparison of different assimilation methodologies of groundwater levels to improve predictions of root zone soil moisture with an integrated terrestrial system model. Advances in Water Resources, 111, 224 - 238. DOI: 10.1016/j.advwatres.2017.11.003.
Identification
Title(s):Main Title: Comparison of different assimilation methodologies of groundwater levels to improve predictions of root zone soil moisture with an integrated terrestrial system model
Description(s):Abstract: The linkage between root zone soil moisture and groundwater is either neglected or simplified in most land surface models. The fully-coupled subsurface-land surface model TerrSysMP including variably saturated groundwater dynamics is used in this work. We test and compare five data assimilation methodologies for assimilating groundwater level data via the ensemble Kalman filter (EnKF) to improve root zone soil moisture estimation with TerrSysMP. Groundwater level data are assimilated in the form of pressure head or soil moisture (set equal to porosity in the saturated zone) to update state vectors. In the five assimilation methodologies, the state vector contains either (i) pressure head, or (ii) log-transformed pressure head, or (iii) soil moisture, or (iv) pressure head for the saturated zone only, or (v) a combination of pressure head and soil moisture, pressure head for the saturated zone and soil moisture for the unsaturated zone. These methodologies are evaluated in synthetic experiments which are performed for different climate conditions, soil types and plant functional types to simulate various root zone soil moisture distributions and groundwater levels. The results demonstrate that EnKF cannot properly handle strongly skewed pressure distributions which are caused by extreme negative pressure heads in the unsaturated zone during dry periods. This problem can only be alleviated by methodology (iii), (iv) and (v). The last approach gives the best results and avoids unphysical updates related to strongly skewed pressure heads in the unsaturated zone. If groundwater level data are assimilated by methodology (iii), EnKF fails to update the state vector containing the soil moisture values if for (almost) all the realizations the observation does not bring significant new information. Synthetic experiments for the joint assimilation of groundwater levels and surface soil moisture support methodology (v) and show great potential for improving the representation of root zone soil moisture.
Identifier(s):DOI: 10.1016/j.advwatres.2017.11.003
Citation Advice:Zhang, H., Kurtz, W., Kollet, S., Vereecken, H., Hendricks Franssen, H.-J. (2018). Comparison of different assimilation methodologies of groundwater levels to improve predictions of root zone soil moisture with an integrated terrestrial system model, Advances in Water Resources, 111, 224-238.
Responsible Party
Creator(s):Author: Hongjuan Zhang
Author: Wolfgang Kurtz
Author: Stefan Kollet
Author: Harry Vereecken
Author: Harrie-Jan Hendricks-Franssen
Publisher:ElSevier
Topic
TR32 Topic:Soil
Related Sub-project(s):C6
Subject(s):CRC/TR32 Keywords: Data Assimilation, Hydrological Modelling
File Details
File Name:Zhang_etal_2017_AWR.pdf
Data Type:Text
File Size:1997 kB (1.95 MB)
Date(s):Date Accepted: 2017-11-03
Mime Type:application/pdf
Data Format:PDF
Language:English
Status:Completed
Constraints
Download Permission:OnlyTR32
General Access and Use Conditions:According to the TR32DB data policy agreement.
Access Limitations:According to the TR32DB data policy agreement.
Licence:TR32DB Data policy agreement
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Measurement Region:None
Measurement Location:--None--
Specific Informations - Publication
Status:Accepted
Review:PeerReview
Year:2018
Type:Article
Article Type:Journal
Source:Advances in Water Resources
Volume:111
Page Range:224 - 238
Metadata Details
Metadata Creator:Wolfgang Kurtz
Metadata Created:2017-12-20
Metadata Last Updated:2017-12-20
Subproject:C6
Funding Phase:3
Metadata Language:English
Metadata Version:V42
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