Abstract
Soil moisture content is one of the most important parameters of hydrological studies. Cosmic-ray neutron sensing is a promising proximal soil moisture sensing technique at intermediate scale and high temporal resolution. In this study, we validate satellite soil moisture products for the period of March 2015 and December 2018 by using several existing Cosmic Ray Neutron Probe (CRNP) stations of the COSMOS database and a CRNP station that was installed in the south part of Turkey in October 2016. Soil moisture values, which were inferred from the CRNP station in Turkey, are also validated using a time domain reflectometer (TDR) installed at the same location and soil water content values obtained from a land surface model (Noah LSM) at various depths (0.1 m, 0.3 m, 0.6 m and 1.0 m). The CRNP has a very good correlation with TDR where both measurements show consistent changes in soil moisture due to storm events. Satellite soil moisture products obtained from the Soil Moisture and Ocean Salinity (SMOS), the METOP-A/B Advanced Scatterometer (ASCAT), Soil Moisture Active Passive (SMAP), Advanced Microwave Scanning Radiometer 2 (AMSR2), Climate Change Initiative (CCI) and a global land surface model Global Land Data Assimilation System (GLDAS) are compared with the soil moisture values obtained from CRNP stations. Coefficient of determination ( r 2 ) and unbiased root mean square error (ubRMSE) are used as the statistical measures. Triple Collocation (TC) was also performed by considering soil moisture values obtained from different soil moisture products and the CRNPs. The validation results are mainly influenced by the location of the sensor and the soil moisture retrieval algorithm of satellite products. The SMAP surface product produces the highest correlations and lowest errors especially in semi-arid areas whereas the ASCAT product provides better results in vegetated areas. Both global and local land surface models’ outputs are highly compatible with the CRNP soil moisture values.
Highlights
Soil water content is one of the most influential variables that is used in the decision support systems of land and water management studies
Root Mean Square Error is 0.07 m3 /m3. These results are in good agreement with the results of [15] in which in situ measurements from the FLUXNET observational network were used in the validation of the Advanced Scatterometer (ASCAT) soil moisture product
It should be noted that the areal representativeness of Cosmic Ray Neutron Probe (CRNP) is still much lower than the footprint of coarse resolution satellite soil moisture products, this spatial mismatch affects the correlations between satellite products and CRNP
Summary
Soil water content is one of the most influential variables that is used in the decision support systems of land and water management studies. Error characterization of soil moisture products is important because of the following reasons: (i) the result of the validation can be used as feedback for algorithm developers for further improvements in the retrieval of soil moisture; (ii) to facilitate understanding of the status of the product for potential users, such as the accuracy, magnitude and the uncertainties of the remote sensing products. Both are very important as they help in better understanding their potential use for practical applications like numerical weather prediction, rainfall estimation, flood forecasting, drought monitoring and prediction [7]
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