气候变化领域集成服务门户(CCPortal): Assessment of SMOS and SMAP soil moisture products against new estimates combining physical model, a statistical model, and in-situ observations: A case study over the Huai River Basin, China

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DOI	10.1016/j.jhydrol.2021.126468
	Assessment of SMOS and SMAP soil moisture products against new estimates combining physical model, a statistical model, and in-situ observations: A case study over the Huai River Basin, China
	Wang, Xiaoyi; Lu, Haishen; Crow, Wade T.; Zhu, Yonghua; Wang, Qimeng; Su, Jianbin; Zheng, Jingyao; Gou, Qiqi
通讯作者	Lu, HS (通讯作者)
发表日期	2021
ISSN	0022-1694
EISSN	1879-2707
卷号	598
英文摘要	Soil moisture often governs the exchange of water between the land surface and the atmosphere and, as a result, has a profound effect on the global water and energy cycles. With the launch of the two new L-band satellite missions tasked with retrieving surface soil moisture (i.e., Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active/Passive (SMAP) missions), new possibilities exist for quasi-global soil moisture monitoring. Here, new soil moisture estimates (CLDAS-BPNN), generated by fusing a land surface model soil moisture product (CLDAS) using in-situ observations via a Back Propagation Neural Network (BPNN) method, are used to evaluate four satellite-derived soil moisture products (SMOS-L3, SMOS-IC, SMAP_L3_SM_P, and SMAP_L3_SM_P_E) over the highly irrigated Huai River Basin in China. Results indicate that the post-processing of CLDAS (to generate CLDAS-BPNN) reduces soil moisture errors (particularly bias) and preserves temporal correlations with in-situ observations. Due to extensive irrigation present in the basin, CLDAS-BPNN soil moisture time series have weak seasonal differences and the spatial distribution of their means does not reflect known precipitation patterns. Based on the validation of SMOS and SMAP soil moisture retrievals against CLDAS-BPNN, several key findings can be obtained. First, SMAP retrievals are recommended for locations possessing both valid SMOS and SMAP retrievals. However, SMOS provides generally better spatial support than SMAP. Second, the four satellite retrievals present no significant seasonal variation in time-varying errors, and larger soil moisture underestimation is observed in winter than in summer. Finally, all four satellite products exhibit degraded accuracy in mountainous and forested areas of the Huai River Basin relative to flatter terrain in the Huaibei plain.
关键词	LAND-SURFACE MODEL SPATIOTEMPORAL VARIABILITY BAND SAR AMSR-E NETWORK RAINFALL SIMULATIONS CALIBRATION RETRIEVALS VEGETATION
英文关键词	Soil moisture; BPNN; SMOS; SMAP; Land surface modeled data; Irrigated area
语种	英语
WOS研究方向	Engineering ; Geology ; Water Resources
WOS类目	Engineering, Civil ; Geosciences, Multidisciplinary ; Water Resources
WOS记录号	WOS:000661813200188
来源期刊	JOURNAL OF HYDROLOGY
来源机构	中国科学院青藏高原研究所
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/260269
推荐引用方式 GB/T 7714	Wang, Xiaoyi,Lu, Haishen,Crow, Wade T.,et al. Assessment of SMOS and SMAP soil moisture products against new estimates combining physical model, a statistical model, and in-situ observations: A case study over the Huai River Basin, China[J]. 中国科学院青藏高原研究所,2021,598.
APA	Wang, Xiaoyi.,Lu, Haishen.,Crow, Wade T..,Zhu, Yonghua.,Wang, Qimeng.,...&Gou, Qiqi.(2021).Assessment of SMOS and SMAP soil moisture products against new estimates combining physical model, a statistical model, and in-situ observations: A case study over the Huai River Basin, China.JOURNAL OF HYDROLOGY,598.
MLA	Wang, Xiaoyi,et al."Assessment of SMOS and SMAP soil moisture products against new estimates combining physical model, a statistical model, and in-situ observations: A case study over the Huai River Basin, China".JOURNAL OF HYDROLOGY 598(2021).