In developing a water quality monitoring program, the sampling frequency chosen should be able to reliably detect changes in water quality trends. Three datasets are evaluated for Minimal Detectable Change in surface water quality to examine the loss of trend detectability as sampling frequency decreases for sites within the National Park Service's Sonoran Desert Network by re-sampling the records as quarterly and annual datasets and by superimposing step and linear trends over the natural data to estimate the time it takes the Seasonal Kendall Test to detect trends of a specific threshold. Wilcoxon Rank Sum analyses found that monthly and quarterly sampling consistently draw from the same distribution of trend detection times; however, annual sampling can take significantly longer. Therefore, even with a loss in power from reduced sampling, quarterly sampling of Park waters adequately detects trends (70%) compared to monthly whereas annual sampling is insufficient in trend detection (30%).