Risk assessment in drinking water production using belief functions

Abstract

This paper presents an original method for risk assessment in water treatment, based on belief functions. The risk of producing non-compliant drinking water (i.e., such that one of the quality parameter exceeds the regulation standards), is estimated taking into account the quality parameters of raw water and the process line of the treatment plant (technology, different failure modes and corresponding failure rates). Uncertainty on available data (treatment steps efficiency, failure rates, times to repair and raw water quality) is modeled using belief functions that are combined to compute a degree of confidence that the produced water will meet quality standards. The methodology recovers the classical results (obtained by fault tree analysis) as a limit case when uncertainties on input data are modeled by probabilities, and still provides informative results when only weaker forms of knowledge are available.