Reducing error in water distribution network simulations with field measurements

Reduction of error in water distribution network (WDN) models leads to simulations that are more representative of actual network conditions and allows for more realistic system responses. Technological improvements have resulted in data collection becoming more prevalent in WDNs. This study quantifies the reduction in model error when considering demand uncertainty by incorporating pressure reducing valve (PRV) monitoring, operational monitoring, and supervisory control and data acquisition (SCADA) system data. Model implementation procedures were developed for each of these data types. For this study, outputs obtained by the modeling software EPANET for a WDN model built with hourly measured demands were treated as actual network observations. Pressures simulated by the network model that incorporated all three types of data had less error than pressures simulated by a base model representative of what water managers would use without access to this data. Model improvement varies both spatially and temporally.