Impact of abundance data errors on the uncertainty of an ecological water quality assessment index

Increased awareness about the uncertainty of ecological water quality (EWQ) assessment tools in river management has led to the identification of the underlying uncertainty sources and the quantification of their effect on assessment. More specifically, with respect to macroinvertebrate-based EWQ assessment, use of erroneous abundance data has been identified as a (possible) source of uncertainty. In this paper, the effect of erroneous abundance data on the uncertainty of an EWQ assessment index was investigated. A model simulation based method, the virtual ecologist approach, was used to estimate the impact of abundance data errors on the uncertainty of the Multimetric Macroinvertebrate Index Flanders (MMIF). The results of this study show that the effects of relative small errors on the MMIF and assessment are limited. Additionally, it is observed that uncertainties due to abundance errors increase with decreasing EWQ (i.e. lower MMIF). This is important, since decision-makers typically formulate management actions for rivers with a low EWQ. In short, the innovative virtual ecologist approach proved to be very successful to research the index uncertainty and present a unique insight in the functioning of the assessment index.