Abstract
Evaluating the reliability of satellite-based and reanalysis soil moisture products is very important in soil moisture research. The traditional methods of evaluating soil moisture products rely on the verification of satellite inversion data and ground observation; however, the ground measurement data is often difficult to obtain. The triple collocation (TC) method can be used to evaluate the accuracy of a product without obtaining the ground measurement data. This study focused on the whole of Qinghai Province, China (31°–40° N, 89°–103° E), and used the TC method to obtain the error variance for satellite-based soil moisture data, the signal-to-noise ratio (SNR) of the same data, and the correlation between the same data and the ground-truth soil moisture, using passive satellite products: Soil Moisture Active Passive (SMAP), Soil Moisture Ocean Salinity (SMOS), Fengyun-3B Microwave Radiation Imager (FY3B), Fengyun-3C Microwave Radiation Imager (FY3C), and Advanced Microwave Scanning Radiometer 2 (AMSR2); an active satellite product Advanced Scatterometer (ASCAT), and reanalysis data Goddard Earth Observing System Model version 5 (GEOS-5) land modeling system. The TC results for the passive satellite data were then compared with the satellite-derived enhanced vegetation index (EVI) to explore the influence of vegetation coverage on the results. The following conclusions are drawn: (1) for the SMAP, SMOS, FY3B, FY3C, and AMSR2 satellite data, the spatial distributions of the TC-derived error variance, the SNR of the satellite-derived soil moisture, and the correlation coefficient between the satellite-derived and ground-truth soil moisture, were all relatively similar, which indirectly verified the reliability of the TC method; and (2) SMOS data have poor applicability for the estimation of soil moisture in Qinghai Province due to their insufficient detection capability in the Qaidam area, high error variance (median 0.0053), high SNR (median 0.43), and low correlation coefficient with ground-truth soil moisture (median 0.57).
Highlights
Surface soil moisture, though accounting for less than 0.001% of global freshwater, plays an important role in the global surface water circulation [1]
It can be seen that surfaces with very low vegetation coverage reduce the Figure 11 shows the correlations between the enhanced vegetation index (EVI) data and the triple collocation (TC) correlation coefficients quality of soil moisture datasets obtained from passive remote sensing satellite data
(correlation between the passive data and the true soil moisture) for the Soil Moisture Active Passive (SMAP), Soil Moisture Ocean Salinity (SMOS), Fengyun-3B Microwave Radiation Imager (FY3B), Fengyun-3C Microwave Radiation Imager (FY3C), microwave radiation is attenuated by vegetation on the soil surface, and microwave radiation from this and Advanced Microwave Scanning Radiometer 2 (AMSR2) passive data
Summary
Though accounting for less than 0.001% of global freshwater, plays an important role in the global surface water circulation [1]. Surface soil moisture plays an important role in soil microbial respiration [3], the biogeochemical cycle [4], crop yield [5], dust generation [6], and disease transmission [7]. Surface soil moisture can be used to monitor deep soil moisture due to the strong correlation between surface soil moisture and deep soil moisture [8]. Efficient monitoring of surface soil moisture is necessary. It is challenging to observe soil moisture due to its variability in space and time
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