Hydro power modelling is important to facilitate the integration of large amounts of variable renewable energy. However, appropriately modelling hydro power presents challenges due to its interconnections with both electricity and river systems. The aim of this paper is to investigate the performance of two selected open-source energy modelling tools for hydro power planning, SpineOpt and PyPSA, with a focus on user-friendliness, accuracy and execution time. In this study, a small river system with two hydro power plants is modelled to maximize the revenue using both tools. At the same time, this linear optimization problem is implemented by Gurobi directly, such that results and execution times from SpineOpt and PyPSA are compared with this baseline. In conclusion, both open-source tools can appropriately model the hydro power system, with SpineOpt having a unique graphical interface and PyPSA has a good performance in execution speed.