Online modelling of water distribution system using Data Assimilation
© 2013 The Authors. Published by Elsevier Ltd. Open access under CC BY-NC-ND license.
This paper applies Data Assimilation (DA) methods to a Water Distribution System Model to improve the realtime estimation of water demand, and hydraulic system states. A time series model is used to forecast water demands which are used to drive the hydraulic model to predict the future system state. Both water demands and water demand model parameters are corrected via DA methods to update the system state. The results indicate that DA methods improved offline hydraulic modelling predictions. Of the DA methods, the Ensemble Kalman Filter outperformed the Kalman Filter in term of updating demands and water demand model parameters. © 2013 The Authors.
The authors are grateful to United Utilities (UU), Mr D. Clucas, Mr T. Allen, Mr N. Croxton and UU hydraulic modelling team for providing the case study data and supporting financially the STREAM EngD project.
12th International Conference on Computing and Control for the Water Industry, CCWI2013
Vol. 70, pp. 1261- 1270