Abstract
This article addresses the issue of estimating probability of misclassification (PoM), when assessing the status of a water body (w.b.). The standard deviation of a monitoring data is considered a good measure of the uncertainty of the assessed w.b. status. However, when PoM is to be estimated from the biological data, a problem caused by too few monitoring data emerges. The problem is overcome by developing Monte-Carlo models to simulate sufficient synthetic measurements of these elements, thereby accounting for random "disturbances" in the measurements. At each level of a procedure, called the Hierarchical Approach, values of PoM were derived from the Monte-Carlo-simulated data as for the assessment of w.b. status. It is assumed in the Hierarchical Approach that PoMs on each upper level can be estimated by processing PoMs inherited from the lower levels. Data from the river monitoring systems in three Polish regions were used in the study. Values of PoM calculated for biological elements show that 70-80% of cases belong to < 0.0, 0.1 > interval, whereas PoMs for physico-chemical elements in only 20% belong in this interval whereas for 25-40% of cases, PoMs are greater than 0.5. Moreover, when analyzing PoMs for cases when the w.b. status was classified as good, 22-52% of them are characterized by 0.5 or higher probability to be assessed wrongly. These pessimistic results suggest the need for formulation of new directions for future research in determining the PoM (in general, the uncertainty) of the w.b. status estimated from monitoring data.