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Article

A Semi-Physical Approach for Downscaling Satellite Soil Moisture Data in a Typical Cold Alpine Area, Northwest China

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Key Laboratory of Ministry of Education on Virtual Geographic Environment, Nanjing Normal University, Nanjing 210023, China
2
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
*
Author to whom correspondence should be addressed.
Academic Editor: Lionel Jarlan
Remote Sens. 2021, 13(3), 509; https://doi.org/10.3390/rs13030509
Received: 30 December 2020 / Revised: 27 January 2021 / Accepted: 28 January 2021 / Published: 31 January 2021
(This article belongs to the Section Remote Sensing of the Water Cycle)
Microwave remote sensing techniques provide a direct measurement of surface soil moisture (SM), with advantages for all-weather observations and solid physics. However, most satellite microwave soil moisture products fail to meet the requirements of land surface studies for high-resolution surface soil moisture data due to their coarse spatial resolutions. Although many approaches have been proposed to downscale the spatial resolution of satellite soil moisture products, most of them have been tested in flat areas where the surface is relatively homogeneous. Thus, those established approaches are often inapplicable for downscaling in cold alpine areas with complex terrain where multiple factors control the variations in surface soil moisture. In this work, we re-inferred and verified the mathematical assumption behind a semi-physical approach for downscaling satellite soil moisture data and extended this approach for cold alpine areas. Instead of directly deriving SM from proxy variables, this approach relies on a relationship between two standardized variables of SM and apparent thermal inertia (ATI), in which the sub grid standard deviation for SM is estimated by a physical hydraulic model taking soil texture data as input. The approach was applied to downscale the soil moisture active passive (SMAP) daily data in a typical cold alpine basin, i.e., the Babao River basin located in the Qilian Mountains of Northwest China. We observed good linearity between the computed ATI and SM observations on most wireless sensor network sites installed in the study basin, which justifies the underlying assumption. The sub grid standard deviations for the SMAP grid estimated through the Mualem-van Genuchten model can broadly represent the real characteristics. The downscaled 1-km resolution results correlated well with the in-situ SM observations, with an average correlation coefficient of 0.74 and a small root mean square error (0.096 cm3/cm3). The downscaled results show more and consistent textural details than the original SMAP data. After removal of biases in the original SMAP data even higher agreements with the observations can be achieved. These results demonstrate the adequacy of the proposed semi-physical approach for downscaling satellite soil moisture data in cold alpine areas, and the resultant fine-resolution data can serve as useful databases for land surface and hydrological studies in those areas. View Full-Text
Keywords: soil moisture; statistical downscaling; semi-physical approach; cold alpine area; sub grid variability; apparent thermal inertia soil moisture; statistical downscaling; semi-physical approach; cold alpine area; sub grid variability; apparent thermal inertia
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MDPI and ACS Style

Cao, Z.; Gao, H.; Nan, Z.; Zhao, Y.; Yin, Z. A Semi-Physical Approach for Downscaling Satellite Soil Moisture Data in a Typical Cold Alpine Area, Northwest China. Remote Sens. 2021, 13, 509. https://doi.org/10.3390/rs13030509

AMA Style

Cao Z, Gao H, Nan Z, Zhao Y, Yin Z. A Semi-Physical Approach for Downscaling Satellite Soil Moisture Data in a Typical Cold Alpine Area, Northwest China. Remote Sensing. 2021; 13(3):509. https://doi.org/10.3390/rs13030509

Chicago/Turabian Style

Cao, Zetao, Hongxia Gao, Zhuotong Nan, Yi Zhao, and Ziyun Yin. 2021. "A Semi-Physical Approach for Downscaling Satellite Soil Moisture Data in a Typical Cold Alpine Area, Northwest China" Remote Sensing 13, no. 3: 509. https://doi.org/10.3390/rs13030509

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