Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction

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Title:Main Title: Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction
Description:Abstract: In situ soil moisture sensors provide highly accurate but very local soil moisture measurements, while remotely sensed soil moisture is strongly affected by vegetation and surface roughness. In contrast, cosmic-ray neutron sensors (CRNSs) allow highly accurate soil moisture estimation on the field scale which could be valuable to improve land surface model predictions. In this study, the potential of a network of CRNSs installed in the 2354 km2 Rur catchment (Germany) for estimating soil hydraulic parameters and improving soil moisture states was tested. Data measured by the CRNSs were assimilated with the local ensemble transform Kalman filter in the Community Land Model version 4.5. Data of four, eight and nine CRNSs were assimilated for the years 2011 and 2012 (with and without soil hydraulic parameter estimation), followed by a verification year 2013 without data assimilation. This was done using (i) a regional high-resolution soil map, (ii) the FAO soil map and (iii) an erroneous, biased soil map as input information for the simulations. For the regional soil map, soil moisture characterization was only improved in the assimilation period but not in the verification period. For the FAO soil map and the biased soil map, soil moisture predictions improved strongly to a root mean square error of 0.03 cm3 cm−3 for the assimilation period and 0.05 cm3 cm−3 for the evaluation period. Improvements were limited by the measurement error of CRNSs (0.03 cm3 cm−3). The positive results obtained with data assimilation of nine CRNSs were confirmed by the jackknife experiments with four and eight CRNSs used for assimilation. The results demonstrate that assimilated data of a CRNS network can improve the characterization of soil moisture content on the catchment scale by updating spatially distributed soil hydraulic parameters of a land surface model.
Identifier:10.5194/hess-21-2509-2017 (DOI)
Citation Advice:Baatz, R., Hendricks Franssen, H.-J., Han, X., Hoar, T., Bogena, H. R., and Vereecken, H.: Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction, Hydrol. Earth Syst. Sci., 21, 2509-2530, https://doi.org/10.5194/hess-21-2509-2017, 2017.
Responsible Party
Creators:Roland Baatz (Author), Harrie-Jan Hendricks-Franssen (Author), Xujun Han (Author), Hoar Tim (Author), Heye Bogena (Author), Harry Vereecken (Author)
Publication Year:2017
TR32 Topic:Soil
Related Subproject:C6
Subjects:Keywords: Data Assimilation, Land-Atmosphere Interaction, Soil Moisture
File Details
Data Type:Text - Article
File Size:5.2 MB
Date:Available: 16.05.2017
Mime Type:application/pdf
Data Format:PDF
Download Permission:Free
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
Specific Information - Publication
Publication Status:Accepted
Review Status:Peer reviewed
Publication Type:Article
Article Type:Journal
Source:Hydrology and Earth System Sciences
Number of Pages:22 (2509 - 2530)
Metadata Details
Metadata Creator:Wolfgang Kurtz
Metadata Created:06.10.2017
Metadata Last Updated:06.10.2017
Funding Phase:2
Metadata Language:English
Metadata Version:V50
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