Stochastic end-use modelling of greywater reuse and rainwater harvesting systems in buildings

Decentralised water supply systems such as rainwater harvesting (RWH) and greywater reuse (GWR) are increasingly implemented to reduce water demand and manage urban runoff. However, existing simulation approaches typically rely on daily water balances and lack high-resolution end-use demand profiles, limiting their ability to assess broader aspects beyond water conservation. This study presents a process-based modelling framework that integrates decentralised systems with stochastic end-use water demand and wastewater discharge patterns generated by SIMDEUM. The framework operates at high temporal resolution (down to one second) and enables simultaneous evaluation of water savings, energy use, storage sizing, overflow dynamics, stormwater reduction, and changes in wastewater quantity and quality. The tool is designed to be flexible and applicable at building to neighbourhood scales, for both residential and non-residential contexts. The framework was applied to a mid-rise residential building in Dublin, Ireland. RWH reduced mains water demand by only 6.4% (energy intensity 0.33 kWh/m 3 ) due to limited roof area, while GWR achieved a 29.3% reduction, owing to continuous and abundant greywater availability, but with higher energy intensity (1.00 kWh/m 3 ). RWH reduced storm runoff by 93.6%, whereas GWR reduced wastewater discharge by 28.9% but increased effluent concentrations of nitrogen (+41.7%), phosphorus (+45.1%), COD (+39.0%), and BOD 5 (+30.7%). Across configurations, supplying an elevated header tank was more energy-efficient than direct pumping to end-uses, and increasing storage reduced overflow losses while prolonging residence times. The proposed framework provides a usable and transparent tool for assessing the integrated performance of decentralised systems, supporting informed design and policy evaluation.