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Nonparametric Tolerance Limit <br />When the background data set contains greater than 50 percent but less than 100 percent <br />nondetect values and/or its distribution is not normal (or transformed normal), Sanitas applies the <br />nonparametric tolerance limit method. However, this method requires a large number of samples <br />to achieve a false positive rate of 1 percent or less, which is required by CCR Title 27 guidelines. <br />Thus, when the alpha level was higher than 1 percent, the concentration limit was not established <br />and data was compared to established limits in the Waste Discharge Requirements. <br />Nonstatistical Approach <br />When the background data set contains 100 percent nondetect values, Sanitas applies the <br />nonstatistical approach. This approach takes into consideration that if historically a constituent <br />has not been detected, any detection of that constituent would be considered an exceedence. <br />Thus, in these situations (100 percent nondetected values), the tolerance limit is set at "detect", <br />meaning that if a value is detected above its method detection limit, this value is an exceedance <br />of the concentration limit. <br />Intrawell Rank Sum <br />When Intrawell Tolerance Limit analysis is unable to normalize the data and thus a <br />nonparametric analysis is performed, the false positive rate becomes greater than five percent. <br />When this happens, the data is compared to the concentration limit listed in the WDRs, if any. In <br />addition, an Intrawell Rank Sum analysis is performed. This is a nonparametric procedure where <br />the sums of ranked data sets are compared. Subsequent sample data are compared with sampling <br />data from the initial monitoring period of the same well. It is assumed that during the initial <br />monitoring period the well has shown no evidence of contamination nor an increasing trend. <br />This test procedure is used to evaluate whether the historical (background data) and the <br />compliance data have the same median constituent concentration. <br />Trend Analysis <br />Sen's Slope measures the change in constituent concentrations per unit time. Sen's method is <br />not greatly affected by outliers, and the slope can be computed when data are missing. Sen's <br />estimator is closely related to the Mann -Kendall test, which is a nonparametric rank correlation <br />test for trend. The test uses only the relative magnitudes of the data rather than their actual <br />values; therefore, missing values are allowed. Sen's Slope and the Mann -Kendall tests are <br />described in "Statistical Methods for Environmental Pollution Monitoring," Richard O. Gilbert, <br />Van Nostrand Reinhold, New York, 1987. The Mann -Kendall test is recommended in "An <br />Evaluation of Trend Detection Techniques for Use in Water Quality Monitoring Programs," Jim <br />Loftis, et al., (USEPA), 1989. <br />Only data detected at least four times above its PQL are evaluated. Trace values used are the <br />estimated values from the certified analytical reports. A trend analysis was conducted only on <br />data collected from the point data was detected above the PQL. For the Corral Hollow Sanitary <br />Landfill, the null hypothesis is "no statistically significant trend in constituent concentrations." <br />Corral Hollow Landfill D-6 Department of Public Works/Solid Waste <br />1 " Quarter 2012 Groundwater Monitoring County of San Joaquin —April 16, 2012 <br />