Calibration of the SMAP Soil Moisture Retrieval Algorithm to Reduce Bias Over the Amazon Rainforest

Soil moisture (
SM
) is crucial for the Earth's ecosystem, impacting climate and vegetation health. Obtaining in situ observations of
SM
is labor-intensive and complex, particularly in remote and densely vegetated regions like the Amazon rainforest. NASA's soil moisture active and passive (SMAP) mission, utilizing an L-band radiometer, aims to monitor global
SM
. While it has been validated in areas with low vegetation water content (
VWC
) (< 5
${\text{kgm}}^{ - 2}$
), its efficiency in the Amazon, with dense canopies and high
VWC
(> 10
${\text{kgm}}^{ - 2}$
), is limitedly investigated due to scarce in situ measurements. This study assessed and analyzed the SMAP
SM
retrievals in the Amazon, employing the single-channel algorithm and adjusting vegetation optical depth (τ) and single scattering albedo (ω), two key vegetation parameters. It incorporated in situ
SM
observations from three old-growth rainforest locations: Tambopata (Southwest Amazon), Manaus (Central Amazon), and Caxiuana (Eastern Amazon). The SMAP
SM
deviated substantially from the in situ
SM
. However, calibrating τ and ω values, characterized by a lower τ, resulted in better agreement with the in situ measurements. This study emphasizes the pressing need for innovative methodologies to accurately retrieve
SM
in high-
VWC
regions like the Amazon rainforest using SMAP data.