This study examines the relationship between changes in precipitation and temperature and the properties of low streamflow to estimate the potential impact of climate change on design-period low flows and associated Total Maximum Daily Loads (TMDLs) of primary pollutants. Stepwise linear regression is used for predicting the future low-flow statistic 10 , 7 10 , 7 Q over the 21st century. Using Latin Hypercube sampling of parameter estimates, the fractional change in low flow and the resulting change in TMDL of a point-source primary pollutant are estimated for GCM climate predictions; for most predictions, a future reduction in contaminant load will be necessary to meet current water quality standards. Once GCM predictions improve, incorporating future climate scenarios in TMDL planning may preserve minimum water quality standards while avoiding a TMDL reallocation in the future.
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