Neyman-Scott-based water distribution network modelling

residential water demand is one of the most difficult parameters to determine when modelling drinking water distribution networks. it has been proven to be a stochastic process which can be characterised as a series of rectangular pulses having set intensity, duration and frequency. such parameters can be determined using stochastic models such as the neyman-scott rectangular pulse model (nsrpm). nsrpm is based on resolving a non-linear optimisation problem involving theoretical moments of the synthetic demand series (equiprobable) and of the observed moments (field measurements) statistically establishing the measured demand series. nsrpm has been applied to generating local residential demand. however, this model has not been validated for a real distribution network with residential demand aggregation, or compared to traditional methods (which is dealt with here). this paper compares the results of synthetic stochastic demand series (calculated using nsrpm applied to determining pressure and flow rate) to results obtained using traditional simulation methods using the curve of hourly variation in demand and to actual pressure and flow rate measurements. the humaya sector of culiacan, sinaloa, mexico, was used as study area.