Fourth and fifth generation district heating (DH) systems have emerged as major contributors to decarbonise the heat sector. However, questions arise about the future trajectory of their existing older versions, which operate at relatively high temperatures. The transformation pathways and operation of DH networks require accurate but simple models to enable rapid simulation. This paper proposes a method for modelling a steady-state DH network using an open-source tool (TESPy) that numerically solves the system of equations and provides a high degree of flexibility in topology and parameterisation. Furthermore, a calibration method using 12 hours of measured data is proposed, which considers the aggregated heat conduction as the calibration parameter and solves the optimisation problem by reducing the difference between the simulated and measured temperature. A DH system in southern Germany with a 15 minute time resolution dataset for the months of January to March 2022 was used as a case study to validate both methods. For the uncalibrated model, the mean absolute error of feed temperatures at all consumers varies from 0.03 °C to 2.34 °C. After calibration, TESPy was found to obtain a mean absolute temperature error of 0.02 °C to 0.5 °C, excluding the cases with high data uncertainty. The accuracy of the simulated temperature enhanced significantly after calibration, thus validating the proposed model. Additionally, it was also observed that the simulated system is more accurate at rather high mass flow conditions.