This study addresses the escalating challenges posed by forest drought and wildfires, emphasizing the critical need to monitor forest conditions to mitigate associated risks. While traditional optical sensors have proven valuable for vegetation surface water (VSW) assessment, their limitations in regions with persistent cloud cover prompt an exploration of the alternatives. The study advocates the efficacy of Synthetic Aperture Radar (SAR) systems, known for their cloud-penetrating capabilities and sensitivity to changes in dielectric properties. Leveraging Sentinel-1 C-band dual polarization SAR data, the research investigates the impact of Vegetation Surface Water (VSW) on backscatter coefficients in a temperate coniferous forest through the application of generalized linear models. Despite the challenges posed by precipitation and canopy characteristics, the study unveils detectable modulation in backscatter, particularly in VH polarization, indicating the potential of SAR-based methods in forest monitoring. The occurrence of rain on the day of Sentinel-1 image acquisition, and therefore the presence of VSW, triggers an increase of 0.35 dB in VV backscatter, and an increase of 0.45 dB in VH backscatter. The findings underscore the importance of considering surface water content in radar backscatter analyses for accurate biomass estimations and change detection, suggesting avenues for future research and potential correction mechanisms.