Аңдатпа
Algorithms for retrieving Surface Soil Moisture (SSM) from microwave remote sensing are continually refined, necessitating the evaluation of newly released products to identify their optimal applications and potential for improvement. This study evaluates ASCAT H119, SMAP DCA, SMAP MTDCA, SMAP-IB, AMSR2, and SMOS-IC products across Central Asia (CA) using a multi-scenario approach. First, the products were validated against three independent reference datasets: ERA5, ESA CCI (combined), and GLDAS-Noah. Second, Triple Collocation Analysis (TCA) was employed to estimate the Fractional Mean Squared Error (fMSE) and the error variance of each product. Third, Hovmöller diagrams were used to identify regional spatiotemporal trends and anomalies. Additionally, the quality of SSM products was examined in relation to key ecological variables across CA. All evaluations were conducted during the SSM growing season (April–October) from 2016 to 2019. Results showed that SMAP products, particularly SMAP DCA and SMAP-IB, delivered the most accurate SSM estimates, achieving the highest average correlation (0.63 to 0.85), low average bias (−0.059 to −0.077 m 3 m −3 ), and the lowest average ubRMSE (0.030 to 0.049 m 3 m −3 ) across the three reference datasets. ASCAT and AMSR2 exhibited moderate performance, while SMOS-IC performed the weakest overall. All products performed best against ESA CCI, followed by ERA5 and then GLDAS-Noah. The performance ranking derived from TCA was generally consistent with the reference-based validation, except for ASCAT and AMSR2. The proposed evaluation framework offers a reliable alternative for assessing SSM products in regions with sparse ground measurements. This study provides valuable insights for enhancing SSM monitoring, hydrological modeling, and agricultural management in the CA ecosystem. • A multi-scenario framework was developed to evaluate six satellite SSM products in Central Asia. • Key regional environmental variables were analyzed to interpret the performance of SSM products under diverse Central Asian conditions. • SMAP DCA and SMAP-IB emerged as the top-performing products, providing the most accurate and reliable SSM estimates for the region. • ASCAT and AMSR2 showed moderate performance, while SMOS-IC exhibited the weakest overall performance.