Modeled Watershed Runoff Associated with Variations in Precipitation Data, with Implications for Contaminant Fluxes: Initial Results

Precipitation is one of the primary forcing functions of hydrologic and watershed fate and transport models; however, in light of advances in precipitation estimates across watersheds, data remain highly uncertain. A wide variety of simulated and observed precipitation data are available for use in regional air quality models and watershed fate and transport models. Although these single media models can potentially link together to estimate contaminant loadings issuing from watersheds, questions remain concerning how precipitation data from diverse sources used within each model affect water and contaminant mass balances. We assess how two sets of spatially distributed precipitation data, simulated at 12-km grid and 36-km grid resolutions, affect runoff simulated from a spatially distributed grid-based mercury watershed model that has been calibrated using observed precipitation data. We focus on two headwater catchments in the Cape Fear River Basin, NC. Our initial results suggest that precipitation data Golden is a physical scientist, Ecosystems Research Division, U.S. Environmental Protection Agency/ Office of Research and Development/ National Exposure Research Laboratory (USEPA/ORD/NERL), Athens, GA 30605. Knightes is an environmental engineer, Ecosystems Research Division, USEPA/ORD/NERL, Athens, GA 30605. Cooter is a meteorologist, Atmospheric Modeling Division, USEPA/ORD/NERL, Research Triangle Park, NC 27711. Dennis is a senior scientist, Atmospheric Modeling Division, USEPA/ORD/NERL, Research Triangle Park, NC 27711. Email: [email protected]. simulated at a coarse resolution (e.g., 36k-m grid) decreases the efficiency and goodness-of-fit of modeled runoff, but this is watershed specific. Variations in the response to coarse resolution precipitation potentially results from differences in the size and within stream structural modifications of each watershed. These initial results are assessed within the context of a broader project that will also evaluate the effects of radar and empirically-estimated precipitation data sets on modeled runoff and variations in watershed contaminant loading resulting from these diverse precipitation inputs.