Demand and Roughness Estimation in Water Distribution Systems

Abstract

To provide more accurate estimates and account for associated uncertainties, a parameter estimation methodology for water distribution systems (WDSs) that combines demand and parameter estimation processes is proposed. A two-step sequential method for dual estimation of demand and roughness coefficient is presented based on a weighted least-squares scheme using field measurements of pipe flow rates and nodal pressure heads under multiple demand conditions. The uncertainties in the estimated variables and resulting nodal pressure predictions are quantified in terms of confidence limits using the first-order second moment method. The algorithm is applied to two network systems including a midsized real WDS. The two-step sequential model provides accurate and precise estimates while joint estimation provides poor estimates.