干旱区生态环境知识资源中心(Arid): An in-situ data based model to downscale radiometric satellite soil moisture products in the Upper Hunter Region of NSW, Australia

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DOI	10.1016/j.jhydrol.2019.03.014
	An in-situ data based model to downscale radiometric satellite soil moisture products in the Upper Hunter Region of NSW, Australia
	Senanayake, I. P.1; Yeo, I-Y 1,2; Tangdamrongsub, N.3,4; Willgoose, G. R.1; Hancock, G. R.5; Welis, T.1; Fang, B.6; Lakshmi, V 6; Walker, J. P.7
通讯作者	Yeo, I-Y
来源期刊	JOURNAL OF HYDROLOGY
ISSN	0022-1694
EISSN	1879-2707
出版年	2019
卷号	572 页码:820-838
英文摘要	High spatial resolution soil moisture information is important for hydrological, climatic and agricultural applications. The lack of high resolution soil moisture data over large areas at the required accuracy is a major impediment for such applications. This study investigates the feasibility of downscaling satellite soil moisture products to 1 km resolution. This study was undertaken in the semi-arid Goulbum River Catchment, located in south-eastern Australia. The Soil Moisture Active Passive (SMAP)-Enhanced 9 km (L3SMP-E) and Soil Moisture and Ocean Salinity (SMOS) 25 km gridded (SMOS CATDS L3 SM 3-DAY) radiometric products were compared with in-situ soil moisture observations and a regression tree model was developed for downscaling based on thermal inertia theory. Observations from a long-term soil moisture monitoring network were employed to develop a regression tree model between the diurnal temperature difference and the daily mean soil moisture for soils with different clay content and vegetation greenness. Moderate-resolution Imaging Spectroradiometer (MODIS) land surface temperatures were used to estimate the soil moisture at high spatial resolution by disaggregating the satellite soil moisture products through the regression model. The downscaled SMAP-Enhanced 9 km and SMOS 25 km gridded soil moisture products showed unbiased root mean square errors (ubRMSE) of 0.07 and 0.05 cm(3)/cm(3), respectively, against the in-situ data. These ubRMSEs include errors caused by measuring instrument and the scale mismatch between downscaled products and in-situ data. An RMSE of 0.07 cm(3)/cm(3) was observed when comparing the downscaled soil moisture against the passive airborne L-band retrievals. The findings here auger well for the use of satellite remote sensing for the assessment of high resolution soil moisture.
英文关键词	Downscaling Disaggregation Soil moisture SMAP SMOS MODIS
类型	Article
语种	英语
国家	Australia ; USA
收录类别	SCI-E
WOS记录号	WOS:000467891900065
WOS关键词	HIGH-RESOLUTION ; WATER-RESOURCES ; 4 DECADES ; SMOS ; VALIDATION ; RETRIEVAL ; TEMPERATURE ; RAINFALL ; EVAPOTRANSPIRATION ; STABILITY
WOS类目	Engineering, Civil ; Geosciences, Multidisciplinary ; Water Resources
WOS研究方向	Engineering ; Geology ; Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/217142
作者单位	1.Univ Newcastle, Fac Engn & Built Environm, Sch Engn, Callaghan, NSW 2308, Australia; 2.Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA; 3.Univ Maryland, Earth Syst Sci Interdisciplinary Ctr, College Pk, MD 20742 USA; 4.NASA, Goddard Space Flight Ctr, Hydrol Sci Lab, Greenbelt, MD 20771 USA; 5.Univ Newcastle, Fac Sci, Sch Environm & Life Sci, Callaghan, NSW 2308, Australia; 6.Univ Virginia, Dept Engn Syst & Environm, Charlottesville, VA 22904 USA; 7.Monash Univ, Dept Civil Engn, Clayton, Vic 3800, Australia
推荐引用方式 GB/T 7714	Senanayake, I. P.,Yeo, I-Y,Tangdamrongsub, N.,et al. An in-situ data based model to downscale radiometric satellite soil moisture products in the Upper Hunter Region of NSW, Australia[J],2019,572:820-838.
APA	Senanayake, I. P..,Yeo, I-Y.,Tangdamrongsub, N..,Willgoose, G. R..,Hancock, G. R..,...&Walker, J. P..(2019).An in-situ data based model to downscale radiometric satellite soil moisture products in the Upper Hunter Region of NSW, Australia.JOURNAL OF HYDROLOGY,572,820-838.
MLA	Senanayake, I. P.,et al."An in-situ data based model to downscale radiometric satellite soil moisture products in the Upper Hunter Region of NSW, Australia".JOURNAL OF HYDROLOGY 572(2019):820-838.