Water distribution systems (WDSs) construction, operation and disposal processes contribute to undesirable greenhouse gas (GHG) emissions. GHG concentration in the atmosphere is strongly associated with global warming and climate change. In order to meet the consequent challenge of limiting GHG emissions, the problem of WDS (re)design is formulated here as a multi-objective optimisation problem. The three objectives are as follows: (1) minimisation of total (re)design cost, (2) maximisation of the WDS resilience and, (3) minimisation of GHGs emissions. In addition to the frequently considered conventional (re)design intervention options (new pipes, pipe duplication or replacement, addition of pumps, tanks, etc.), various water demand management interventions (e.g. water efficient appliances and domestic Rainwater Harvesting Systems) are considered here too. A number of different rainwater tank sizes and water saving appliances provided to different parts of the households have been evaluated. This methodology was applied on the New York Tunnels and the Anytown network problems. The output from the Non-dominated Sorting Genetic Algorithm (NSGA2) optimisation process is a Pareto front containing optimal solutions traded-off in terms of the three objectives analysed. The results obtained demonstrate that using demand management technologies in the (re)design of WDSs can lead to a similar cost, resilience and GHG emissions but with cost savings. In a pumped WDS where cost savings and GHG emission reduction are relatively significant, demand management technologies led to more cost effective, resilient and climate change mitigating solutions as compared to the conventional (re)design.