Simulation-Based Localized Sensitivity Analyses (SaLSA) — An Example of Water Quality Failures in Distribution Networks

Models for environmental, socio-political, engineering and economic systems are typically complex due to a large number of interacting factors. Uncertainty and sensitivity analyses are integral parts of modelling complex systems. The level of uncertainties associated with any system increases with system complexity. These uncertainties are a result of vaguely known relationships among various factors (epistemic), as well as randomness in the mechanisms governing the domain (aleatory). Uncertainty analysis examines variations in the results that are imparted by the uncertainties in inputs, whereas sensitivity analysis determines the contributions of inputs. This paper discusses the identification of predominant input factors and ranking them using a technique called, Simulation-based Localized Sensitivity Analysis (SaLSA), which is a hybrid of a `differential analysis' and `simulation-based sampling' techniques. The proposed sensitivity analyses results are discussed using an example of water quality failures in distribution networks.