Soil moisture experiment in the Luan River supporting new satellite mission opportunities

Zhao, Tianjie; Shi, Jiancheng; Lv, Liqing; Xu, Honggang; Chen, Deqing; Cui, Qian; Jackson, Thomas J.; Yan, Guangjian; Li, Jia; Chen, Liangfu; Zhao, Kai; Zheng, Xunhua; Zhao, Limin; Zheng, Chaolei; Ji, Dabin; Xiong, Chao; Wang, Tianxing; Li, Rui; Pan, Jinmei; Wen, Jianguang; Yu, Chao; Zheng, Yunpu; Jiang, Lingmei; Chai, Linna; Lu, Hui; Yao, Panpan; Ma, Jinzhu; Lü, Haishen; Wu, Jianjun; Zhao, Wei; Yang, Na; Guo, Pan; Li, Yuxia; Hu, Lu; Geng, Deyuan; Zhang, Ziqian

doi:10.1016/j.rse.2020.111680

Cited by 139 publications

(83 citation statements)

References 73 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In China, long-term evaluation of satellite SM products were mainly conducted over the alpine meadow in the cold semiarid regions of Qinghai-Tibet Plateau [25][26][27], relying on the multi-scale SM and soil temperature monitoring networks, such as Tibet-Obs and Soil Moisture and Temperature Monitoring Network on the central TP (CTP-SMTMN) since 2002 [28,29]. In recent years, new soil moisture experiments are conducted outside Tibetan plateau on the scale of watershed in support of the hydrological cycle studies [30,31]. Currently, the evaluation and comparison works are still focused on the scale of watershed in China [16,32].…”

mentioning

confidence: 99%

Evaluation of SMAP, SMOS, and AMSR2 Soil Moisture Products Based on Distributed Ground Observation Network in Cold and Arid Regions of China

Wang¹,

Che²,

Zhao³

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Self Cite

View full text Add to dashboard Cite

Long-term surface soil moisture (SM) data are increasingly needed in water budget and energy balance analysis of watersheds. The performance of nine remotely sensed SM products from AMSR2, SMOS and SMAP missions, are evaluated based on observations collected from distributed observation networks in the Heihe River Basin (HRB) of China during 2013 to 2017. Results show that the SMAP Level 3 Dual Channel Algorithm (DCA) SM retrievals reflect the seasonal SM variations well with high temporal correlations of ~0.7 and high accuracy within 0.04 m 3 /m 3 in terms of unbiased Root Mean Squared Error (ubRMSE) over the grassland in the HRB. The SMOS level 3 SM retrievals present increased underestimation and ubRMSE of ~0.10 m 3 /m 3 as the vegetation increases. The newly published SMOS-IC product in version 2 outperforms the SMOS level 3 product with improved temporal correlation coefficient above 0.4 and lower ubRMSE of ~0.05 m 3 /m 3 . AMSR2 Land Parameter Retrieval Algorithm (LPRM) SM products show extremely large overestimation over the vegetated regions in HRB, especially the C-band products. Drastically high underestimation biases are observed in the Japan Aerospace Exploration Agency (JAXA) AMSR2 SM product. Parameter uncertainty analyses indicate that the different parameterization schemes of vegetation optical depth (VOD) inputs could be one of the main reasons resulting in the systematic overestimation/underestimation biases in the AMSR2/SMOS/SMAP SM retrievals. The findings aim to provide insights into studies on algorithms refinements and data fusions of SM products in HRB.

show abstract

mentioning

confidence: 99%

Evaluation of SMAP, SMOS, and AMSR2 Soil Moisture Products Based on Distributed Ground Observation Network in Cold and Arid Regions of China

Wang¹,

Che²,

Zhao³

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Self Cite

View full text Add to dashboard Cite

show abstract

“…Considering different sensing depths in the SMOSREX revealed that the agreement in soil moisture between the model-predicted data with consideration of the brightness temperature in the L band and measured data was satisfactory at depth of 0–5 cm which is concurrent with global surface soil moisture provided by the SMOS satellite 23 . In the case of spatially variable soils, the compliance of soil moisture from satellite and ground measurements in soil profile can be improved by using combined active, passive microwave and optical methods, with different penetration depths in airborne flights 43 . On the other hand, the obtained real and imaginary dielectric constants from the measurements of the SMOS brightness temperature allow to determine penetration depth and soil moisture using available methods 23 , 28 , 42 .…”

Section: Discussionmentioning

confidence: 99%

The SMOS-Derived Soil Water EXtent and equivalent layer thickness facilitate determination of soil water resources

Usowicz

Łukowski

Lipiec

2020

Sci Rep

View full text Add to dashboard Cite

The assessment of water resources in soil is important in understanding the water cycle in the natural environment and the processes of water exchange between the soil and the atmosphere. The main objective of the study was to assess water resources (in 2010–2013) in the topsoil from satellite (SMOS) and in situ (ground) measurements using the SWEX_PD approach (Soil Water EXtent at Penetration Depth). The SWEX_PD is a result of multiplying soil moisture (SM) and radiation penetration depth (PD) for each pixel derived from the SMOS satellite. The PD, being a manifold of the wavelength λ0 equal to 21 cm, was determined from the weekly SMOS L2 measurement data based on the real and imaginary part of complex dielectric constant. The SWEX_PD data were compared with soil water resources (WR) calculated from the sum of components derived from multiplication of soil moisture (SM) and layer thickness in nine agrometeorological stations located along the eastern border of Poland. Each study site consisted of seven neighbouring Discrete Global Grid pixels (nodes spaced at 15 km) including the central ones with agrometeorological stations. The study area included different types of soils and land covers. The agreement between the water resources obtained from the SWEX_PD and ground measurements (WR) was quantified using classical statistics and Bland–Altman's plots. Calibrated Layer Thickness (CLT = dbias) from 8 to 28 cm was obtained with a low values of bias (close to zero), limits of agreements, and confidence intervals for all the SWEX_PD, depending on the pixel location. The results revealed that the use of the SWEX_PD for assessing soil water resources is the most reliable approach in the study area. Additionally, the data from Bland–Altman plots and the equation proposed in these studies allowed calculation of the Equivalent Layer Thickness (ELT = $$d_{ei}^{SWEX}$$ d ei SWEX ), which corresponds to the water resources derived from the SMOS satellite at the same time as (SM) measurements performed in the agrometeorological stations. The ranges of the mean, standard deviation, minimum, maximum, and coefficient of variation (CV) of ELT among all pixels and stations were 8.28–28.7 cm, 3.27–12.66 cm, 3.03–10.87 cm, 19.23–94.97 cm, and 24.72–98.79%, respectively. The ranges of the characteristics depended on environmental conditions and their means were close to the values of the calibrated layer thickness. The impacts of soil texture, organic matter, vegetation, and their interactive effects on the differentiation and agreement of soil water resources obtained from SWEX_PD vs. data from ground measurements in the study area are discussed. Further studies are required to address the impact of the environmental factors to improve the assessment of soil water resources based on satellite SM products (retrievals).

show abstract

“…SMOS-HR is a CNES-sponsored follow-on to SMOS, offering 10 km resolution and advanced RFI mitigation techniques, and has recently entered Phase A of its mission. Other missions targeting water cycle with L-Band include the Chinese WCOM [44] and the TWRS [45] satellites.…”

Section: E Complementarity With Other Missionsmentioning

confidence: 99%

An Introduction to the HydroGNSS GNSS Reflectometry Remote Sensing Mission

Unwin

Pierdicca

Cardellach

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

HydroGNSS has been selected as the second ESA Scout Earth Observation mission to demonstrate the capability of small satellites to deliver science. This paper summarises the case for HydroGNSS, as developed during its System Consolidation study. HydroGNSS is a high value dual small satellite mission, which will prove new concepts and offer timely climate observations that supplement and complement existing observations and are high in ESA's Earth Observation scientific priorities. The mission delivers observations of four hydrological Essential Climate Variables (ECVs) as defined by the Global Climate Observing System (GCOS) using the new technique of GNSS Reflectometry. These will cover the world's land mass to 25 km resolution, with a 15 day revisit. The variables are soil moisture, inundation or wetlands, freeze / thaw state and above ground biomass.

show abstract

Soil moisture experiment in the Luan River supporting new satellite mission opportunities

Cited by 139 publications

References 73 publications

Evaluation of SMAP, SMOS, and AMSR2 Soil Moisture Products Based on Distributed Ground Observation Network in Cold and Arid Regions of China

Evaluation of SMAP, SMOS, and AMSR2 Soil Moisture Products Based on Distributed Ground Observation Network in Cold and Arid Regions of China

The SMOS-Derived Soil Water EXtent and equivalent layer thickness facilitate determination of soil water resources

An Introduction to the HydroGNSS GNSS Reflectometry Remote Sensing Mission

Contact Info

Product

Resources

About