| Sumario: | We use basic characteristics of statistical significance test to argue the abandonment of hypothesis testing in environmental standard (or criterion) compliance assessment. The typical sample size used for environmental assessment is small, and the natural variation of many water quality constituent concentrations is high. These conditions lead to low statistical power of the hypothesis tests used in the assessment process. As a result, using hypothesis testing is often inefficient in detecting noncompliance. When a noncompliance is detected, it is frequently due to sampling or other types of error. We illustrate the problems using two examples, through which we argue that these problems cannot be resolved under the current practice of assessing compliance one water at a time. We recommend that the hypothesis testing framework be replaced by a statistical estimation approach, which can more effectively leverage information from assessments on similar waters using a probabilistic assessment approach.
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