In the efforts to decarbonise the heat sector, heat pumps can offer a cost-effective transition away from fossil fuels. Water Source Heat Pumps (WSHP) can be utilised in cases where ambient water sources (river, ground water, abandoned mines water) are present. However, the economic benefits of different levels of heat pump centralisation as well as their comparative advantages over other decentralised options such as individual Air Source Heat Pumps (ASHP) or Gas Boilers (GB) remain uncertain and further investigations are necessary to fully assess their potential. This study introduces CATHeaPS, a Centralisation Analysis Tool for Heat Pump Systems, a user-friendly open access modelling tool that enables the technoeconomic assessment of (a) district heating networks with a centralised WSHP, and (b) ambient networks with decentralised building level WSHPs against individual ASHPs and GB for a range of consumer classes. CATHeaPS provides a complete project cashflow for each supply option and is verified against published data and outputs from a UK industrial case study, with slightly altered data to ensure confidentiality. A data analysis highlights the break-even points for the number of residential properties, beyond which centralised solutions are more economic than decentralised energy supply options for different housing densities. A thorough sensitivity analysis is also conducted to identify the impact of different input parameters on the levelised cost of energy of each supply option. It is found that discount rate has the largest impact for both networks, followed by CAPEX and energy costs. This study aims to help stakeholders and decision makers in two ways. It introduces a novel, easy-to-use open access technoeconomic tool that enables a high-level analysis of energy, hydraulic and economic factors for any project area. Furthermore, it maps the boundaries of beneficial operation for different levels of centralisation for residential consumers and gives preliminary suggestions on which energy supply option is better suited to a given project.