Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
doi:10.5194/hess-2016-478
© Author(s) 2016. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
14 Oct 2016
Review status
A revision of this discussion paper is under review for the journal Hydrology and Earth System Sciences (HESS).
Multi-source hydrological soil moisture state estimation using data fusion optimisation
Lu Zhuo and Dawei Han WEMRC, Department of Civil Engineering, University of Bristol, Bristol, UK
Abstract. Reliable estimation of hydrological soil moisture state is of critical importance in operational hydrology to improve the flood prediction and hydrological cycle description. Although there have been a number of soil moisture products, they cannot be directly used in hydrological modelling. This paper attempts for the first time to build a soil moisture product directly applicable to hydrology using multiple data sources retrieved from SAC-SMA (soil moisture), MODIS (land surface temperature), and SMOS (multi-angle brightness temperatures in H–V polarisations). The simple yet effective Local Linear Regression model is applied for the data fusion purpose in the Pontiac catchment. Four schemes according to temporal availabilities of the data sources are developed, which are pre-assessed and best selected by using the well-proven feature selection algorithm Gamma Test. The hydrological accuracy of the produced soil moisture data is evaluated against the Xinanjiang hydrological model's soil moisture deficit simulation. The result shows that a superior performance is obtained from the scheme with the data inputs from all sources (NSE = 0.912, r = 0.960, RMSE = 0.007 m). Additionally the final daily-available hydrological soil moisture product significantly increases the Nash–Sutcliffe efficiency by almost 50 % in comparison with the two most popular soil moisture products. The proposed method could be easily applied to other catchments and fields with high confidence. The misconception between the hydrological soil moisture state variable and the real-world soil moisture content, and the potential to build a global routine hydrological soil moisture product are discussed.

Citation: Zhuo, L. and Han, D.: Multi-source hydrological soil moisture state estimation using data fusion optimisation, Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-478, in review, 2016.
Lu Zhuo and Dawei Han
Lu Zhuo and Dawei Han
Lu Zhuo and Dawei Han

Viewed

Total article views: 373 (including HTML, PDF, and XML)

HTML PDF XML Total BibTeX EndNote
246 108 19 373 12 20

Views and downloads (calculated since 14 Oct 2016)

Cumulative views and downloads (calculated since 14 Oct 2016)

Viewed (geographical distribution)

Total article views: 373 (including HTML, PDF, and XML)

Thereof 372 with geography defined and 1 with unknown origin.

Country # Views %
  • 1

Saved

Discussed

Latest update: 27 May 2017
Publications Copernicus
Download
Share