A time-series analysis approach developed by the U.S. Geological Survey was used to analyze trends in total phosphorus and evaluate optimal sampling designs for future trend detection, using long-term data for two water-quality monitoring stations on the Quinebaug River in eastern Connecticut. Trend-analysis results for selected periods of record during 1971?2001 indicate that concentrations of total phosphorus in the Quinebaug River have varied over time, but have decreased significantly since the 1970s and 1980s. Total phosphorus concentrations at both stations increased in the late 1990s and early 2000s, but were still substantially lower than historical levels. Drainage areas for both stations are primarily forested, but water quality at both stations is affected by point discharges from municipal wastewater-treatment facilities. Various designs with sampling frequencies ranging from 4 to 11 samples per year were compared to the trend-detection power of the monthly (12-sample) design to determine the most efficient configuration of months to sample for a given annual sampling frequency. Results from this evaluation indicate that the current (2004) 8-sample schedule for the two Quinebaug stations, with monthly sampling from May to September and bimonthly sampling for the remainder of the year, is not the most efficient 8-sample design for future detection of trends in total phosphorus. Optimal sampling schedules for the two stations differ, but in both cases, trend-detection power generally is greater among 8-sample designs that include monthly sampling in fall and winter. Sampling designs with fewer than 8 samples per year generally provide a low level of probability for detection of trends in total phosphorus. Managers may determine an acceptable level of probability for trend detection within the context of the multiple objectives of the state?s water-quality management program and the scientific understanding of the watersheds in question. Managers may identify a threshold of probability for trend detection that is high enough to justify the agency?s investment in the water-quality sampling program. Results from an analysis of optimal sampling designs can provide an important component of information for the decision-making process in which sampling schedules are periodically reviewed and revised. Results from the study described in this report and previous studies indicate that optimal sampling schedules for trend detection may differ substantially for different stations and constituents. A more comprehensive statewide evaluation of sampling schedules for key stations and constituents could provide useful information for any redesign of the schedule for water-quality monitoring in the Quinebaug River Basin and elsewhere in the state.