Uncertainty and Risk Inclusions in Water Distribution Systems Management: Review and Challenges

Abstract

The typical high number of constraints and decision variables, the nonlinearity, and the non-smoothness of the head-flow-water quality governing equations are inherent to water distribution systems, which make their problem solutions a complex task. Recent methodologies are employing heuristic optimization techniques such as genetic algorithms or ant colony as stand alone or hybrid data driven-heuristic frameworks. Almost all models treat the data and variables as deterministic. Uncertainty inclusion in water distribution systems simulation and management is in its infancy. This paper briefly reviews the current state of the art on the inclusion of uncertainty and risk in water distribution systems management models, and suggests future challenges on this topic.