Microwave vegetation optical depth (VOD) and soil moisture (SM) can be simultaneously retrieved based on L-band radiometry with polarization information. VOD is indicative of the vegetation water content (VWC) because it captures the extinction of land surface emission. If the connectivity of VOD to VWC is robust, the pair of VWC-SM observations can be viable bases for understanding soil-plant-atmosphere water relations, providing new perspectives on ecosystem science. Simultaneous SM-VOD retrievals are feasible by inverting the − model with two independent datasets in dual channel algorithms. However, given correlated satellite vertical and horizontal brightness temperatures (TBv and TBh), an ill-posed inverse problem arises where TB errors result in high uncertainties of retrievals. In this study, we apply the Degrees-of-Information (DoI) metric and propose a Signal-to-Noise Ratio (SNR) metric to assess the "retrievability" of VOD given the SMAP TBv-TBh linear dependence. The application of these metrics allows determiningwhere the VOD retrievals are robust and reliable. This is a necessary step in supporting applications of VOD in ecology and hydrology. Results show that regions with mainly non-woody vegetation have the best potential for VOD retrievals, though regularization is necessary. We then assess VOD time variations from two regularization products that reduce the impact of underdetermined inversions: the L3-DCA and the MTDCA, which constrain VOD time dynamics with and without using a priori VOD climatology, respectively. Though they both reduce noise, especially in the VOD retrievals, they result in differences in VOD seasonal amplitude and coupling to SM at high frequencies as we outline here.