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<br />0137 <br /> <br />stations 07105500 Fountain Creek at Colorado Springs and 07105905 Fountain <br />Creek below Fountain. The median concentration of most constituents at <br />station 07105500 Fountain Creek at Colorado Springs, downstream from the mouth <br />of Monument Creek, is more similar to the median concentration of most <br />constituents at station 07104905 Monument Creek at Bijou than to the median <br />concentration of most constituents at station 07103700 Fountain Creek near <br />Colorado Springs, indicating that the water quality of Monument Creek has a <br />large effect on the water quality of Fountain Creek. <br /> <br />To determine the effect of the Colorado Springs Wastewater-Treatment <br />Plant on the water quality of Fountain Creek, station 07105500 Fountain Creek <br />at Colorado Springs, upstream from the wastewater-treatment plant, and station <br />07105530 Fountain Creek below CSWWTP were compared. Tukey's test results <br />indicated that there were no statistically significant differences in the <br />water quality between the two stations for the following property and <br />constituents: water temperature, nitrite plus nitrate as nitrogen, and fecal <br />coliform bacteria. The following properties and constituents had statisti- <br />cally significant increases downstream: instantaneous streamflow, specific <br />conductance, total ammonia as nitrogen, un-ionized ammonia as nitrogen, total <br />recoverable copper, total recoverable zinc, and 5-day BOD. The following <br />properties and constituents had statistically significant decreases down- <br />stream: pH, dissolved oxygen, suspended solids, and total recoverable iron. <br /> <br />Time-Series Trends <br /> <br />Time-series trends at each station were analyzed to determine if changes <br />in the values of water-quality properties and concentrations of constituents <br />had occurred over time. Factors such as land use, water use, and climate in <br />the basin can affect water quality. Detection of temporal trends in water <br />quality can indicate changes in the factors that affect water quality. <br /> <br />Trend analysis of time-series data for water-quality properties and <br />constituents is complicated by several common characteristics of the data: <br />nonnormality, seasonality, serial dependence, and censoring. Nonnormal data <br />cannot be described by a symmetrical, unimodal, bell-shaped distribution. <br />Seasonal data have a natural sequential order over time and vary, depending <br />on the time of year. Water-quality data often are serially dependent; the <br />constituent concentration at one point in time is dependent upon and related <br />to prior data. Censored data contain less-than values due to the detection <br />limits of the analytical methods. <br /> <br />The seasonal Kendall test, which was used in this study to detect <br />temporal trends in water quality, is based on methods developed by the U.S. <br />Geological Survey (Hirsch and Slack, 1984). The seasonal Kendall test is a <br />statistical technique unaffected by the problem characteristics described <br />above (Hirsch and others, 1982; Hirsch and Slack, 1984). This technique is <br />used to identify statistically significant monotonic changes (only increasing <br />or only decreasing trends) in data over time. The technique also provides an <br />estimate of the magnitude and direction of the change, which can be used to <br />calculate the percent change in the median constituent concentration for the <br />period of record. The seasonal Kendall test is a nonparametric statistical <br />technique; the test statistic is determined by using ranks of the data rather <br />than the actual data. Nonnormality of the data set and censored values are <br /> <br />13 <br />