A Two‐Component Mixing Model for Predicting Regional Episodic Acidification of Surface Waters During Spring Snowmelt Periods

Abstract

A two‐component mixing model of acid neutralizing capacity (ANC) is proposed for explaining two observed features related to the episodic acidification of surface waters during snowmelt periods: (1) maximum episodic declines in ANC are largest in high ANC systems and increase linearly with antecedent ANC and (2) relative depressions in ANC attributable to increases in nitric acid concentrations are larger in low ANC systems, while relative depressions in ANC attributable to dilution of base cations are larger in high ANC systems. Conceptually, the model represents the physical mixing of two hydrochemical end‐members within a surface water environment, although the physical sources of water in the model are undefined. The model is shown to explain 55–72% of the total variation of these characteristics among various surface water systems within the Catskill and Adirondack mountain regions of New York. In addition, the model also explains 11–47% of the relative depression in ANC attributable to natural organic acidity in surface waters in these regions. The model is subsequently linked to an empirical equilibrium acidification model for predicting the long‐term episodic acidification response of Adirondack lakes during snowmelt periods. Model predictions suggest that percentage decreases in sulfuric acid concentrations of the magnitude mandated by the 1990 Clean Air Act Amendments (40%) will not restore to positive values the ANC of all Adirondack lakes which are currently acidic (ANC < 0) during spring snowmelt periods. Long‐term increases in nitric acid concentrations may counterbalance the expected increases in ANC attributable to reductions in sulfur deposition.