Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/hess-2016-617
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
30 Nov 2016
Review status
This discussion paper is a preprint. It has been under review for the journal Hydrology and Earth System Sciences (HESS). The manuscript was not accepted for further review after discussion.
Upscaling of soil moisture content from surface to profile: multi-station testing of observation operators
Xiaodong Gao1,2,3, Xining Zhao1,2,3, Luca Brocca4, Ting Lv3, Gaopeng Huo3, and Pute Wu1,2,3 1Institute of Soil and Water Conservation, Northwest A&F University, Yangling, Shaanxi Province, China
2Institute of Soil and Water Conservation, CAS and MWR, Yangling, Shaanxi Province, China
3National Engineering Research Center for Water Saving Irrigation at Yangling, Yangling, Shaanxi, China
4Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, Italy
Abstract. The accurate assessment of profile soil moisture for spatial domains is usually difficult due to the associated costs, strong spatial-temporal variability, and nonlinear relationship between surface and profile moisture. Here we attempted to use observation operators built by Cumulative Distribution Frequency (CDF) matching method to directly upscale surface observations to profile soil moisture based on multi-station in situ measurements from the Soil and Climate Analysis Network (SCAN). We first analyzed the effects of temporal resolution (hourly, daily and weekly) and data length (half year in non-growing season, half year in growing season, one year, two years and four years) on the performance of observation operators. The results showed that temporal resolution had a negligible influence on the performance of observation operators. However, data length significantly changed the prediction accuracy of observation operators; prediction errors decreased as data length increased from half year (non-growing season) to two years, but accuracy did not further improve at longer interval. A dataset with a two-year duration was therefore used to test the robustness of observation operators in three primary climates (humid continental, humid subtropical and semiarid) of the continental USA, with the popular exponential filter employed as a reference approach. The results indicated that observation operators generally performed better than exponential filter method in both calibration and validation periods. This suggests that observation operators are a robust statistical tool for upscaling soil moisture from surface to profile. The findings here may be applied in the prediction of profile soil moisture from surface measurements obtained via various means, including remote sensing techniques.

Citation: Gao, X., Zhao, X., Brocca, L., Lv, T., Huo, G., and Wu, P.: Upscaling of soil moisture content from surface to profile: multi-station testing of observation operators, Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-617, 2016.
Xiaodong Gao et al.
Interactive discussionStatus: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version      Supplement - Supplement
 
AC1: 'Erratum', Xining Zhao, 06 Dec 2016 Printer-friendly Version Supplement 
 
RC1: 'Review of "Upscaling of soil moisture content from surface to profile: multistation testing of observation operators" by Gao et al.', Na Li, 03 Jan 2017 Printer-friendly Version 
 
RC2: 'Can CDF matching give such outstanding results?', Wolfgang Wagner, 03 Jan 2017 Printer-friendly Version 
Xiaodong Gao et al.
Xiaodong Gao et al.

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Short summary
We built observation operators by the CDF matching method. Two-year duration was identified as the optimal data length in prediction accuracy. Application in different climates in USA showed these operators are a robust statistical tool for upscaling soil moisture from surface to profile by using exponential filter as a reference method. The findings here may be applied in the prediction of profile soil moisture from surface measurements via remote sensing techniques.
We built observation operators by the CDF matching method. Two-year duration was identified as...
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