Seasonal patterns are evident in surface water chemistry draining forested headwaters in the northeastern United States. This variation in surface water chemistry is largely driven by seasonal fluctuations in hydrologic flow paths and biological activity. Especially during spring snowmelt, high-flow conditions are characterized by high concentrations of NO3-, naturally occurring organic anions and aluminum species, and depression in surface water pH and acid neutralizing capacity (ANC). Under extreme conditions, decreases in pH and ANC and increases in aluminum can have adverse effects on aquatic biota. As a result, there is a critical need to be able to simulate seasonal variations in surface water acid-base chemistry. Previously, a single soil layer biogeochemical model (PnET-BGC) was found to be inadequate to simulate seasonal variations in stream chemistry draining acid-sensitive forest watersheds. In order to better simulate the seasonal variations in the acid-base chemistry of surface waters, a two-layer model (PnET-BGC2) was formulated and applied to a northern forest ecosystem. End-member mixing analysis was used to better understand hydrologic flow paths contributing to temporal patterns in stream chemistry and to parameterize the model. The resulting two-layer model is generally able to reproduce the seasonal variations in surface water runoff, concentrations of base cations, SO42-, NO3-, pH, and ANC.