Abstract
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 Advanced Microwave Scanning Radiometer 2 (AMSR2), Soil Moisture and Ocean Salinity (SMOS), and Soil Moisture Active Passive (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 SM retrievals reflect the seasonal SM variations well with high temporal correlations of ∼0.7 and high accuracy within 0.04 m3/m3 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 m3/m3 as the vegetation increases. The newly published SMOS Institut National de la Recherche Agronomique–Centre d'Etudes Spatiales de la BIOsphere product in version 2 outperforms the SMOS level 3 product with improved temporal correlation coefficient above 0.4 and lower ubRMSE of ∼0.05 m3/m3. AMSR2 Land Parameter Retrieval Algorithm 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 AMSR2 SM product. Parameter uncertainty analyses indicate that the different parameterization schemes of vegetation optical depth 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.
Highlights
Surface soil moisture (SM) is a key variable in landatmosphere interactions affecting the land surface energy, water budget and the carbon cycle at a global, regional and watershed scale
The Advanced Microwave Scanning Radiometer 2 (AMSR2) onboard the Global Change Observation Mission-Water (GCOM-W1) satellite launched in 2012 [5], is the successor of AMSR-E which enable the distribution of the first global standard SM products with the resolution of 25km at both Cand X-band [6]
This research aims to provide a comprehensive evaluation of nine passive microwave remotely sensed SM products over the diverse land cover and land surface conditions in Heihe River Basin (HRB), and the error source analyses are conducted from the perspective of parameterization in SM retrieval algorithms to provide new insights into the various performances of these SM products and to help obtaining long-term and highly accurate data sets for regional hydrological and climatic studies in future
Summary
Surface soil moisture (SM) is a key variable in landatmosphere interactions affecting the land surface energy, water budget and the carbon cycle at a global, regional and watershed scale. The currently operated passive microwave satellites/sensors provide continuously updated observations at various spatial and temporal resolutions. Other two SM monitoring satellites include the Soil Moisture and Ocean Salinity (SMOS) and the Soil Moisture Active Passive (SMAP), which were successively launched in 2009 and 2015, respectively. Both of them are expected to achieve more accurate SM products due to the higher capability of L-band in penetrating vegetation and soil compared to the C- or X-band technologies [7, 8]
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