Multi-Scale Validation of SMAP Soil Moisture Products over Cold and Arid Regions in Northwestern China Using Distributed Ground Observation Data

The Soil Moisture Active Passive (SMAP) mission was designed to provide global mapping of soil moisture (SM) on nested 3, 9, and 36 km earth grids measured by L-band passive and active microwave sensors. The validation of SMAP SM products is crucial for the application of the products and improvement of the retrieval algorithm. Since the SMAP SM products were released, much effort has been invested in the evaluation of the SMAP radiometer SM product (SMAP_P). However, there has been little validation of SMAP radar (SMAP_A) and active/passive combined (SMAP_AP) SM products. This paper presents an evaluation of SMAP_P, SMAP_A and SMAP_AP SM products by using distributed ground observations networks in different landscapes in the Heihe River Basin of northwestern China. The standard error metrics of SMAP products and relative error are applied to measure the products’ performances. The results show that the SMAP SM products exhibit consistent spatial-temporal variation with the ground measurements and typical precipitation events. Three products show various types of performance capability (e.g., active, passive and combined), surface coverage (e.g., bare, vegetated) and climatic region (e.g., cold, arid). Relatively, the SMAP_P shows the best performance, while the SMAP_A performs the worst. The best performances are observed over bare soils but with overestimation and the largest relative error, and unsatisfactory accuracies are observed over cold regions and woody vegetated surfaces with underestimation. The vegetation effect and the freezing-thawing cycle may be major factors that led to an unsatisfactory performance. Efforts on resolving the influence of these factors are expected to improve the accuracy and to promote the application of SMAP SM products over these regions. Overall, this evaluation provides an understanding of SMAP SM products over cold and arid regions, and suggestions for the further refinement of the SMAP SM retrieval algorithms.