![]() A high number of groups of cross-correlated demands, i.e., scenarios, for the entire network were generated using Latin Hypercube Sampling (LHS) and the numerical procedure proposed by Iman and Conover. Besides, consumption at each node is considered to follow a Gamma probability distribution. The scaling laws are employed to determine the statistics of nodal consumption as a function of the number of users and the main statistical features of the unitary user's demand. ![]() This approach makes use of the demand scaling laws in order to consider the natural variability and spatial correlation of nodal consumptions. A numerical approach for generating a limited number of water demand scenarios and estimating their occurrence probabilities in a Water Distribution Network (WDN) is proposed.
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