Time series and recurrence interval models to predict the vulnerability of streams to episodic acidification in Shenandoah National Park, Virginia

Abstract

Acid rain affects headwater streams by temporarily reducing the acid‐neutralizing capacity (ANC) of the water, a process termed episodic acidification. The increase in acidic components in stream water can have deleterious effects on the aquatic biota. Although acidic deposition is uniform across Shenandoah National Park (SNP) in north central Virginia, the stream water quality response during rain events varies substantially. This response is a function of the catchment's underlying geology and topography. Geologic and topographic data for SNP's 231 catchments are readily available; however, long‐term measurements (tens of years) of ANC and accompanying discharge are not and would be prohibitively expensive to collect. Transfer function time series models were developed to predict hourly ANC from discharge for five SNP catchments with long‐term water‐quality and discharge records. Hourly ANC predictions over short time periods (≤1 week) were averaged, and distributions of the recurrence intervals of annual water‐year minimum ANC values were model‐simulated for periods of 6, 24, 72, and 168 hours. The distributions were extrapolated to the rest of the SNP catchments on the basis of catchment geology and topography. On the basis of the models, large numbers of SNP streams have 6‐ to 168‐hour periods of low‐ANC values, which may stress resident fish populations. Smaller catchments are more vulnerable to episodic acidification than larger catchments underlain by the same bedrock. Catchments with similar topography and size are more vulnerable if underlain by less basaltic/carbonate bedrock. Many catchments are predicted to have successive years of low‐ANC values potentially sufficient to extirpate some species.