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Estimating Soil Moisture at High Spatial Resolution with Three Radiometric Satellite Products: A Study from a South-Eastern Australian Catchment
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  • I.P. Senanayake,
  • In-Young Yeo,
  • Natthachet Tangdamrongsub,
  • Garry R. Willgoose,
  • Greg R. Hancock,
  • Tony Wells,
  • Bin Fang,
  • Venkat Lakshmi
I.P. Senanayake

Corresponding Author:indishe@gmail.com

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In-Young Yeo
University of Newcastle
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Natthachet Tangdamrongsub
University of Newcastle
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Garry R. Willgoose
University of Newcastle
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Greg R. Hancock
University of Newcastle
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Tony Wells
University of Newcastle
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Bin Fang
University of South Carolina
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Venkat Lakshmi
University of South Carolina
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Abstract

Long-term soil moisture datasets at high spatial resolution are important in agricultural, hydrological, and climatic applications. The soil moisture estimates can be achieved using satellite remote sensing observations. However, the satellite soil moisture data are typically available at coarse spatial resolutions (~ several tens of km), therefore require further downscaling. Different satellite soil moisture products have to be conjointly employed in developing a consistent time-series of high resolution soil moisture, while the discrepancies amongst different satellite retrievals need to be resolved. This study aims to downscale three different satellite soil moisture products, the Soil Moisture and Ocean Salinity (SMOS, 25 km), the Soil Moisture Active Passive (SMAP, 36 km) and the SMAP-Enhanced (9 km), and to conduct an inter-comparison of the downscaled results. The downscaling approach is developed based on the relationship between the diurnal temperature difference and the daily mean soil moisture content. The approach is applied to two sub-catchments (Krui and Merriwa River) of the Goulburn River catchment in the Upper Hunter region (NSW, Australia) to estimate soil moisture at 1 km resolution for 2015. The three coarse spatial resolution soil moisture products and their downscaled results will be validated with the in-situ observations obtained from the Scaling and Assimilation of Soil Moisture and Streamflow (SASMAS) network. The spatial and temporal patterns of the downscaled results will also be analysed. This study will provide the necessary insights for data selection and bias corrections to maintain the consistency of a long-term high resolution soil moisture dataset. The results will assist in developing a time-series of high resolution soil moisture data over the south-eastern Australia.