The temporal-spatial resolution of input data-induced uncertainty in a watershed-based water quality model, Hydrologic Simulation Program-FORTRAN (HSPF), is investigated in this study. The temporal resolution-induced uncertainty is described using the coefficient of variation (CV). The CV is found to decrease with decreasing temporal resolution and follow a log-normal relation with time interval for temperature data while it exhibits a power-law relation for rainfall data. The temporal-scale uncertainties in the temperature and rainfall data follow a general extreme value distribution and a Weibull distribution, respectively. The Nash-Sutcliffe coefficient (NSC) is employed to represent the spatial resolution induced uncertainty. The spatial resolution uncertainty in the dissolved oxygen and nitrate-nitrogen concentrations simulated using HSPF is observed to follow a general extreme value distribution and a log-normal distribution, respectively. The probability density functions (PDF) provide new insights into the effect of temporal-scale and spatial resolution of input data on uncertainties involved in watershed modelling and total maximum daily load calculations. This study exhibits non-symmetric distributions of uncertainty in water quality modelling, which simplify weather and water quality monitoring and reducing the cost involved in flow and water quality monitoring. Copyright © 2011 John Wiley & Sons, Ltd.