| There is uncertainty associated with characterizing water quality data due to small sample sizes, data being censored, data gaps, and other data issues. Quantification of this uncertainty is critical for making improved decisions. Using a confidence interval of statistical estimates is one way to describe this uncertainty. Bootstrap method, a resampling technique, is easy to implement and can be used to estimate any statistics and their associated confidence intervals. In this study, the performance of the bootstrap and traditional statistical methods in quantifying the uncertainty of complete and censored water quality data was assessed. Several innovative approaches incorporating uncertainty in regulating the toxic pollutants in wastewater discharges were proposed, and the approaches were evaluated using real municipal wastewater treatment plant effluent water quality data. |
