Root-zone soil moisture estimation from assimilation of downscaled Soil Moisture and Ocean Salinity data. (October 2015)

• Record Type: Journal Article
• Authors: Dumedah, Gift; P. Walker, Jeffrey; Merlin, Olivier
• Is Part Of: Advances in water resources. Volume 84(2015)
• Page Start: 14
• Page End: 22
• Publication Date: 2015-10
• Subjects: Root-zone soil moisture -- SMOS -- DisPATCh -- Data assimilation -- Evolutionary strategy; Hydrology -- Periodicals; Hydrodynamics -- Periodicals; Hydraulic engineering -- Periodicals; 551.48
• DOI: 10.1016/j.advwatres.2015.07.021
• Languages: English
• ISSNs: 0309-1708

Abstract

Highlights: Assimilate a downscaled high spatial resolution SMOS data into JULES model. Provide improved root-zone soil moisture from assimilation of downscaled SMOS data. Updated output increased the open loop accuracy by 52% across 3 deeper soil layers. Findings show a positive impact from downscaled SMOS data and the assimilation. Abstract: The crucial role of root-zone soil moisture is widely recognized in land–atmosphere interaction, with direct practical use in hydrology, agriculture and meteorology. But it is difficult to estimate the root-zone soil moisture accurately because of its space-time variability and its nonlinear relationship with surface soil moisture. Typically, direct satellite observations at the surface are extended to estimate the root-zone soil moisture through data assimilation. But the results suffer from low spatial resolution of the satellite observation. While advances have been made recently to downscale the satellite soil moisture from Soil Moisture and Ocean Salinity (SMOS) mission using methods such as the Disaggregation based on Physical And Theoretical scale Change (DisPATCh), the assimilation of such data into high spatial resolution land surface models has not been examined to estimate the root-zone soil moisture. Consequently, this study assimilates the 1-km DisPATCh surface soil moisture into the Joint UK Land Environment Simulator (JULES) to better estimate the root-zone soil moisture. The assimilation is demonstrated using the advanced Evolutionary Data Assimilation (EDA) procedure for the Yanco area in south eastern Australia. When evaluated using in-situ OzNet soil moisture, the open loop was found to be 95% as accurate as the updated output, with the updated estimate improving the DisPATCh data by 14%, all based on the root mean square error (RMSE). Evaluation of the root-zone soil moisture with in-situ OzNet data found the updated output to improve the open loop estimate by 34% for the 0–30 cm soil depth, 59% for the 30–60 cm soil depth, and 63% for the 60–90 cm soil depth, based on RMSE. The increased performance of the updated output over the open loop estimate is associated with (i) consistent estimation accuracy across the three soil depths for the updated output, and (ii) the deterioration of the open loop output for deeper soil depths. Thus, the findings point to a combined positive impact from the DisPATCh data and the EDA procedure, which together provide an improved soil moisture with consistent accuracy both at the surface and at the root-zone.