Validation of Five Passive Microwave Remotely Sensed Soil Moisture Products over the Qinghai-Tibet Plateau, China

The Qinghai-Tibet Plateau (QTP) holds massive freshwater resources and is one of the most active regions in the world with respect to the hydrological cycle. Soil moisture (SM) plays a critical role in hydrological processes and is important for plant growth and ecosystem stability. To investigate the relationship between climatic factors (air temperature and precipitation) and SM during the growing season in various climate zones on the QTP, data from three observational stations were analyzed. The results showed that the daily average (Tave) and minimum air temperatures (Tmin) significantly influenced SM levels at all depths analyzed (i.e., 10, 20, 30, 40, and 50 cm deep) at the three stations, and Tmin had a stronger effect on SM than did Tave. However, the daily maximum air temperature (Tmax) generally had little effect on SM, although it had showed some effects on SM in the middle and deeper layers at the Jiali station. Precipitation was an important factor that significantly influenced the SM at all depths at the three stations, but the influence on SM in the middle and deep layers lagged the direct effect on near-surface SM by 5–7 days. These results suggest that environment characterized by lower temperatures and higher precipitation may promote SM conservation during the growing season and in turn support ecosystem stability on the QTP.

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Linking thaw depth with soil moisture and plant community composition: effects of permafrost degradation on alpine ecosystems on the Qinghai-Tibet Plateau

Plant and Soil ◽

10.1007/s11104-012-1511-1 ◽

2012 ◽

Vol 367 (1-2) ◽

pp. 687-700 ◽

Cited By ~ 31

Author(s):

Zhao-ping Yang ◽

Ji-xi Gao ◽

Lin Zhao ◽

Xing-liang Xu ◽

Hua Ouyang

Keyword(s):

Soil Moisture ◽

Community Composition ◽

Plant Community ◽

Tibet Plateau ◽

Permafrost Degradation ◽

Plant Community Composition ◽

Alpine Ecosystems ◽

Composition Effects ◽

Thaw Depth ◽

Qinghai Tibet Plateau

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Influences of soil moisture and salt content on loess shear strength in the Xining Basin, northeastern Qinghai-Tibet Plateau

Journal of Mountain Science ◽

10.1007/s11629-018-5206-9 ◽

2019 ◽

Vol 16 (5) ◽

pp. 1184-1197 ◽

Cited By ~ 4

Author(s):

Jiang-tao Fu ◽

Xia-song Hu ◽

Xi-lai Li ◽

Dong-mei Yu ◽

Ya-bin Liu ◽

...

Keyword(s):

Shear Strength ◽

Soil Moisture ◽

Salt Content ◽

Tibet Plateau ◽

Xining Basin ◽

Qinghai Tibet Plateau

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A Spatial and Temporal Continuum Remotely Sensed Soil Moisture Dataset of the Tibet Plateau From 2002 to 2015

10.5194/egusphere-egu2020-20846 ◽

2020 ◽

Author(s):

Yaokui Cui ◽

Chao Zeng ◽

Jie Zhou ◽

Xi Chen

Keyword(s):

Soil Moisture ◽

Tibetan Plateau ◽

Land Surface ◽

European Space Agency ◽

Remotely Sensed ◽

General Regression Neural Network ◽

Tibet Plateau ◽

The Tibetan Plateau ◽

Space Agency ◽

Spatio Temporal

Abstract:Surface soil moisture plays an important role in the exchange of water and energy between the land surface and the atmosphere, and critical to climate change study. The Tibetan Plateau (TP), known as &#8220;The third pole of the world&#8221; and &#8220;Asia&#8217;s water towers&#8221;, exerts huge influences on and sensitive to global climates. Long time series of and spatio-temporal continuum soil moisture is helpful to understand the role of TP in this situation. In this study, a dataset of 14-year (2002&#8211;2015) Spatio-temporal continuum remotely sensed soil moisture of the TP at 0.25&#176; resolution is obtained, combining MODIS optical products and ESA (European Space Agency) ECV (Essential Climate Variable) combined soil moisture products based on General Regression Neural Network (GRNN). The validation of the dataset shows that the soil moisture is well reconstructed with R2 larger than 0.65, and RMSE less than 0.08 cm3 cm-3 and Bias less than 0.07 cm3 cm-3 at 0.25&#176; and 1&#176; spatial scale, compared with the in-situ measurements in the central of TP. And then, spatial&#160;and&#160;temporal&#160;characteristics and trend of SM over TP were analyzed based on this dataset.Keywords: Soil moisture; Remote Sensing; Dataset; GRNN; ECV; Tibetan Plateau

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Active Layer Thickness Retrieval Over the Qinghai-Tibet Plateau Using Sentinel-1 Multitemporal InSAR Monitored Permafrost Subsidence and Temporal-Spatial Multilayer Soil Moisture Data

IEEE Access ◽

10.1109/access.2020.2988482 ◽

2020 ◽

Vol 8 ◽

pp. 84336-84351 ◽

Cited By ~ 2

Author(s):

Xuefei Zhang ◽

Hong Zhang ◽

Chao Wang ◽

Yixian Tang ◽

Bo Zhang ◽

...

Keyword(s):

Soil Moisture ◽

Layer Thickness ◽

Active Layer ◽

Tibet Plateau ◽

Active Layer Thickness ◽

Soil Moisture Data ◽

Qinghai Tibet Plateau

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Evaluation of SMAP, SMOS-IC, FY3B, JAXA, and LPRM Soil Moisture Products over the Qinghai-Tibet Plateau and Its Surrounding Areas

Remote Sensing ◽

10.3390/rs11070792 ◽

2019 ◽

Vol 11 (7) ◽

pp. 792 ◽

Cited By ~ 6

Author(s):

Jin Liu ◽

Linna Chai ◽

Zheng Lu ◽

Shaomin Liu ◽

Yuquan Qu ◽

...

Keyword(s):

Soil Moisture ◽

Land Surface ◽

Regional Scale ◽

Temporal Variations ◽

Comparison Method ◽

Tibet Plateau ◽

Quantitative Evidence ◽

Retrieval Algorithms ◽

Qinghai Tibet Plateau

High-quality and long time-series soil moisture (SM) data are increasingly required for the Qinghai-Tibet Plateau (QTP) to more accurately and effectively assess climate change. In this study, to evaluate the accuracy and effectiveness of SM data, five passive microwave remotely sensed SM products are collected over the QTP, including those from the soil moisture active passive (SMAP), soil moisture and ocean salinity INRA-CESBIO (SMOS-IC), Fengyun-3B microwave radiation image (FY3B), and two SM products derived from the advanced microwave scanning radiometer 2 (AMSR2). The two AMSR2 products are generated by the land parameter retrieval model (LPRM) and the Japan Aerospace Exploration Agency (JAXA) algorithm, respectively. The SM products are evaluated through a two-stage data comparison method. The first stage is direct validation at the grid scale. Five SM products are compared with corresponding in situ measurements at five in situ networks, including Heihe, Naqu, Pali, Maqu, and Ngari. Another stage is indirect validation at the regional scale, where the uncertainties of the data are quantified by using a three-cornered hat (TCH) method. The results at the regional scale indicate that soil moisture is underestimated by JAXA and overestimated by LPRM, some noise is contained in temporal variations in SMOS-IC, and FY3B has relatively low absolute accuracy. The uncertainty of SMAP is the lowest among the five products over the entire QTP. In the SM map composed by five SM products with the lowest pixel-level uncertainty, 66.64% of the area is covered by SMAP (JAXA: 19.39%, FY3B: 10.83%, LPRM: 2.11%, and SMOS-IC: 1.03%). This study reveals some of the reasons for the different performances of these five SM products, mainly from the perspective of the parameterization schemes of their corresponding retrieval algorithms. Specifically, the parameterization configurations and corresponding input datasets, including the land-surface temperature, the vegetation optical depth, and the soil dielectric mixing model are analyzed and discussed. This study provides quantitative evidence to better understand the uncertainties of SM products and explain errors that originate from the retrieval algorithms.

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