Water quality variability can be examined to estimate the magnitude of changes in water quality needed to detect significant differences over time. Adjustments can be made to reduce the estimate of variability, thereby decreasing the water quality change required for statistical significance. These adjustments include: accounting for changes in meteorologic and hydrologic conditions through covariate variables in trend analyses; changing the sampling frequency; increasing the number of years in the monitoring scheme; and use of other statistical trend analyses, such as t-tests, linear regression, and time series analyses. Water quality monitoring data was examined from the Idaho Rural Clean Water Program (RCWP) project. Generally, a 30 to 60 percent change in unadjusted geometric mean concentrations is required to document a significant change in water quality. However, adjustments that reduce the estimate of variability can be used to reduce the required concentration change to 20 to 40 percent.