Calibration Assessment and Data Collection for Water Distribution Networks

Abstract

Calibration of a water distribution network is intended to develop a model that mimics field conditions under a range of demand distributions. In this paper, a three-step calibration procedure is developed that considers the uncertainties in measurement and estimation and provides a measure of the quality of the calibration. The approach can also be used to identify preferable conditions for data collection. The procedure's steps are parameter estimation, calibration assessment, and data collection design. Parameter estimation considers input uncertainty and the resulting uncertainty in model parameters. Calibration assessment analyzes the propagation of the parameter errors on model predictions. The trace of the covariance matrix of the predictive heads is used to measure the model uncertainty. Based on this uncertainty and using a sensitivity-based heuristic analysis, data collection experiments can be designed for systemwide tests and critical pipe for individual pipe tests. An example system is analyzed to select calibration demand conditions.