The paper compares the two most common methods of data reconciliation for pipeline networks. The first method, an unscented Kalman filter (UKF), uses a system of nonlinear implicit ordinary differential equations derived from the governing partial differential equations. The second method, a quadratic program, relies on a transformation of the system of nonlinear ordinary differential equations into a set of linear difference equations, with the linearization optimized for known pressure and flow ranges using a novel linearization technique. Both the UKF and the quadratic programming approaches for data reconciliation in gas pipeline networks are viable for networks of small to moderate size. Given the reduced number of simplifying assumptions and the resulting improved accuracy, the UKF may be preferable when the computational problem is tractable. The quadratic programming approach is faster, accepts lower fidelity models, and provides acceptable accuracy. (C) 2018 Elsevier Ltd. All rights reserved.