2020 journal article
Reducing error in water distribution network simulations with field measurements
JOURNAL OF APPLIED WATER ENGINEERING AND RESEARCH, 8(1), 15–27.
author keywords: Boundary condition; data collection; uncertainty reduction; water distribution modeling
TL;DR:
This study quantifies the reduction in model error when considering demand uncertainty by incorporating pressure reducing valve monitoring, operational monitoring, and supervisory control and data acquisition (SCADA) system data.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
6. Clean Water and Sanitation
(Web of Science; OpenAlex)
Source: Web Of Science
Added: February 27, 2020
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.