Linking air quality and watershed models for environmental assessments: Analysis of the effects of model-specific precipitation estimates on calculated water flux

Directly linking air quality and watershed models could provide an effective method for estimating spatially-explicit inputs of atmospheric contaminants to watershed biogeochemical models. However, to adequately link air and watershed models for wet deposition estimates, each model's temporal and spatial representation of precipitation needs to be consistent. We explore how precipitation implemented within the Community Multi-Scale Air Quality Model (CMAQ) model algorithms, and multiple spatially-explicit precipitation datasets that could be used to improve the CMAQ model deposition estimates, links with the standard precipitation sources used to calibrate watershed models (i.e., rain gage data) via modeled water fluxes. Simulations are run using a grid-based watershed mercury model (GBMM) in two watersheds. Modeled monthly runoff suggests that multiple resolution Parameter-elevations Regressions on Independent Slopes Model (PRISM) and National Multi-sensor Precipitation Analysis Stage IV (NPA) data generate similar monthly runoff estimates, with comparable or greater accuracy when evaluated against stream gage data than that produced by the base rain gage data. However, across longer time periods, simulated water balances using 36 km Pennsylvania State University/National Center for Atmospheric Research mesoscale model (MM5) data are similar to that of base data. The investigation also examines the implications our results, providing suggestions for linking air quality and watershed fate and transport models. Published by Elsevier Ltd.