State and parameter estimation of two land surface models using the ensemble Kalman filter and the particle filter

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Title:Main Title: State and parameter estimation of two land surface models using the ensemble Kalman filter and the particle filter
Description:Abstract: Land surface models (LSMs) use a large cohort of parameters and state variables to simulate the water and energy balance at the soil–atmosphere interface. Many of these model parameters cannot be measured directly in the field, and require calibration against measured fluxes of carbon dioxide, sensible and/or latent heat, and/or observations of the thermal and/or moisture state of the soil. Here, we evaluate the usefulness and applicability of four different data assimilation methods for joint parameter and state estimation of the Variable Infiltration Capacity Model (VIC-3L) and the Community Land Model (CLM) using a 5-month calibration (assimilation) period (March–July 2012) of arealaveraged SPADE soil moisture measurements at 5, 20, and 50 cm depths in the Rollesbroich experimental test site in the Eifel mountain range in western Germany. We used the EnKF with state augmentation or dual estimation, respectively, and the residual resampling PF with a simple, statistically deficient, or more sophisticated, MCMC-based parameter resampling method. The performance of the “calibrated” LSM models was investigated using SPADE water content measurements of a 5-month evaluation period (August–December 2012). As expected, all DA methods enhance the ability of the VIC and CLM models to describe spatiotemporal patterns of moisture storage within the vadose zone of the Rollesbroich site, particularly if the maximum baseflow velocity (VIC) or fractions of sand, clay, and organic matter of each layer (CLM) are estimated jointly with the model states of each soil layer. The differences between the soil moisture simulations of VIC-3L and CLM are much larger than the discrepancies among the four data assimilation methods. The EnKF with state augmentation or dual estimation yields the best performance of VIC-3L and CLM during the calibration and evaluation period, yet results are in close agreement with the PF using MCMC resampling. Overall, CLM demonstrated the best performance for the Rollesbroich site. The large systematic underestimation of water storage at 50 cm depth by VIC-3L during the first few months of the evaluation period questions, in part, the validity of its fixed water table depth at the bottom of the modeled soil domain.
Identifier:10.5194/hess-21-4927-2017 (DOI)
Responsible Party
Creators:Hongjuan Zhang (Author), Harrie-Jan Hendricks-Franssen (Author), Xujun Han (Author), Jasper A. Vrugt (Author), Harry Vereecken (Author)
Publisher:European Geosciences Union
Publication Year:2019
Topic
TR32 Topic:Soil
Related Subproject:C6
Subjects:Keywords: LSM, Data Assimilation, Soil Moisture
File Details
Filename:zhangetal_2017a.pdf
Data Type:Text - Article
File Size:14.8 MB
Dates:Accepted: 19.07.2017
Available: 29.09.2017
Mime Type:application/pdf
Data Format:PDF
Language:English
Status:Completed
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Download Permission:Only Project Members
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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Specific Information - Publication
Publication Status:Published
Review Status:Peer reviewed
Publication Type:Article
Article Type:Journal
Source:Hydrol. Earth Syst. Sci.
Volume:21
Number of Pages:32 (4927 - 4958)
Metadata Details
Metadata Creator:Tanja Kramm
Metadata Created:31.01.2019
Metadata Last Updated:31.01.2019
Subproject:C6
Funding Phase:3
Metadata Language:English
Metadata Version:V50
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