<p>Intensified acidification has emerged as an increasing threat to the health of global coastal ecosystems, and decreasing pH trends have been observed in Chinese coastal waters. However, the drivers in complex regions like Hangzhou Bay remain poorly understood due to the lack of high-resolution time-series data. Thus, utilizing two years of hourly data (2019–2020) from two buoy stations, this study analyzes the key variables driving pH variability and develops a high-performance support vector regression (SVR) model for pH estimation, which achieves a coefficient of determination (<i>R</i>²) of 0.72 on an independent testing dataset. This model was then used to reconstruct a continuous daily sea surface pH dataset, which reveals a clear seasonal pH cycle with minimums in summer and maximums in winter. This pattern arises from a complex interplay among multiple factors. River runoff is the dominant influence in summer, whereas temperature and biological activity primarily shape the pH patterns in other seasons. The pronounced pH variability and the strong, runoff-driven summer minimum highlight the region’s heightened vulnerability to episodic acidification. This work provides key insights into the drivers of sea surface pH in Hangzhou Bay, improving the understanding of the nearshore carbonate system and its ecological responses to global change in a complex estuarine environment.</p>