TY - JOUR
T1 - Multivariate Statistical Analysis for Water Demand Modeling
AU - Notaro, Vincenza
AU - Fontanazza, Chiara Maria
AU - Puleo, Valeria
AU - Freni, null
AU - Fontanazza, Chiara Maria
AU - Puleo, Valeria
AU - Notaro, null
PY - 2014
Y1 - 2014
N2 - The actual level of water demand is the driving force behind the hydraulic dynamics in water distribution systems. Consequently, it is crucial to estimate it as accurately as possible in order to result in reliable simulation models. In this paper, a copula-based multivariate analysis has been proposed and used for demand prediction for given return period. The analysis is applied to water consumption data collected in the water distribution network of Palermo (Italy). The approach showed to produce consisted demand patterns and to be a powerful tool to be coupled with water distribution network models for design or analysis problems. (C) 2014 Published by Elsevier Ltd.
AB - The actual level of water demand is the driving force behind the hydraulic dynamics in water distribution systems. Consequently, it is crucial to estimate it as accurately as possible in order to result in reliable simulation models. In this paper, a copula-based multivariate analysis has been proposed and used for demand prediction for given return period. The analysis is applied to water consumption data collected in the water distribution network of Palermo (Italy). The approach showed to produce consisted demand patterns and to be a powerful tool to be coupled with water distribution network models for design or analysis problems. (C) 2014 Published by Elsevier Ltd.
UR - http://hdl.handle.net/10447/355248
UR - https://www.sciencedirect.com/science/article/pii/S1877705814026381
M3 - Article
VL - 89
SP - 901
EP - 908
JO - Procedia Engineering
JF - Procedia Engineering
SN - 1877-7058
ER -