Modeling spatial diffusion of decentralized water technologies and impacts on the urban water systems

Abstract

Understanding the market demand for decentralized water technologies and the impacts on the urban water systems (UWS) is critical to sustainable promotion in urban communities. In this paper, we developed a spatial agent-based model (ABM) that simulates the adoption of home-based rainwater harvesting (RWH) and greywater recycling (GWR) by single-family households in Boston, United States. We applied system dynamics modeling (SDM) to evaluate the impacts of decentralized technologies on the UWS. The change in carbon emissions of the UWS was modeled as the environmental benefit for household choice decisions in ABM. We validated our integration by comparing the simulated reservoir elevations with the reference-year values and comparing where early adoptions emerge with the reported installations. In the results, we first examined the sensitivity of the adoption and diffusion to the market promotion, neighbor's influence, environmental benefits, and economic attractiveness. Our simulation highlights the diffusion from central downtown to the suburban. RWH has higher adoptions than GWR, and RWH starts diffusing much earlier. Reservoir water availability is improved through the adoption of RWH and GWR. As the tradeoffs, reservoirs discharge more water for storage security, and hydropower generation becomes less as the need of water transfer decreases. The UWS do not reduce carbon emissions due to the high electricity consumption of GWR. Utilizing the improved water resources and reducing the impact of decentralized technologies are required for sustainable promotion of water decentralization. Our integrated modeling can be improved by including more critical socio-technical interactions for spatial planning of decentralized water technologies.