Salinization of freshwaters by human activities is of growing concern globally. Consequences of salt pollution include adverse effects to aquatic biodiversity, ecosystem function, human health, and ecosystem services. In headwater streams of the temperate forests of eastern USA, elevated specific conductance (SC), a surrogate measurement for the major dissolved ions composing salinity, has been linked to decreased diversity of aquatic insects. However, such linkages have typically been based on limited numbers of SC measurements that do not quantify intra-annual variation. Effective management of salinization requires tools to accurately monitor and predict salinity while accounting for temporal variability. Toward that end, high-frequency SC data were collected within the central Appalachian coalfield over 4 years at 25 forested headwater streams spanning a gradient of salinity. A sinusoidal periodic function was used to model the annual cycle of SC, averaged across years and streams. The resultant model revealed that, on average, salinity deviated approximately ±20% from annual mean levels across all years and streams, with minimum SC occurring in late winter and peak SC occurring in late summer. The pattern was evident in headwater streams influenced by surface coal mining, unmined headwater reference streams with low salinity, and larger-order salinized rivers draining the study area. The pattern was strongly responsive to varying seasonal dilution as driven by catchment evapotranspiration, an effect that was amplified slightly in unmined catchments with greater relative forest cover. Evaluation of alternative sampling intervals indicated that discrete sampling can approximate the model performance afforded by high-frequency data but model error increases rapidly as discrete sampling intervals exceed 30 days. This study demonstrates that intra-annual variation of salinity in temperate forested headwater streams of Appalachia USA follows a natural seasonal pattern, driven by interactive influences on water quantity and quality of climate, geology, and terrestrial vegetation. Because climatic and vegetation dynamics vary annually in a seasonal, cyclic manner, a periodic function can be used to fit a sinusoidal model to the salinity pattern. The model framework used here is broadly applicable in systems with streamflow-dependent chronic salinity stress.
Water Research – Elsevier
Published: Apr 15, 2018
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