**1. Introduction**

Urban water utility systems around the world are increasingly pressured by limited water resources, growing urban demand, and impacts from climate change. The United Nations projects that, by 2025, 1.8 billion people will be living in regions with absolute water scarcity, and two-thirds of the world population could be living under water-stressed conditions [1]. Supply-side strategies for urban water management are limited in water-scarce regimes, because they require large investments to construct new infrastructure and develop new resources. Demand-side strategies, on the other hand, extend existing resources by reducing demands through conservation campaigns, pricing strategies, and restrictions. Demand-side strategies that rely on continued demand reduction, however, are ultimately limited by hardened demands that cannot be reduced further. As water scarcity in urban centers increases with population growth and climate change, new technologies, advanced management strategies, and diverse water sources must emerge to create new efficiencies in water supply and use. Innovative programs can utilize new technologies and data that have emerged as part of smart cities initiatives [2]. For example, smart meters provide capabilities to collect sub-hourly water flow and consumption data in real-time [3], and automated control systems operate infrastructure components remotely and efficiently [4–6].

This manuscript explores a novel management strategy for improving water efficiency in urban areas by supplementing non-potable purposes of the total demand using alternative water sources. A smart water grid is presented here as a water network that is shared by multiple diverse users, who can either produce or consume water. The concept presented in this manuscript builds on an existing dual reticulation system, which pumps non-potable reclaimed water back to a community via a second parallel pipe network and reduces demands for high quality treated water, as compared with a conventional urban water cycle (Figure 1a,b). We propose that the existing non-potable water network can be used as a smart water grid to facilitate micro-trading, where households can exchange water within a peer-to-peer network. Households generate water through rainwater harvesting, putting rainwater "back on the grid" by pumping water into the non-potable water infrastructure system, and purchase water from neighbors by withdrawing water from the pipe network. Smart technologies, such as smart meters, blockchain, smart contracts, and automated infrastructure, would provide the necessary capabilities to allow real-time trading within a smart water grid. Within a smart city paradigm, a rainwater micro-trading program re-envisions the urban water cycle by allowing households to act as prosumers, who produce and sell water within their community (Figure 1c). By allowing households to trade rainwater, a new efficiency is introduced in the water cycle that offsets requirements to treat and pump reclaimed water from a centralized facility. This offset can create energy savings and save reclaimed water for use in other non-potable applications.

In the energy sector, micro-trading has been demonstrated as a viable market for decentralized resource production, in which households can generate energy through solar photovoltaic cells, store energy in batteries, and sell and transmit excess energy to neighbors through existing power distribution infrastructure [7,8]. Micro-trading water has a number of nuanced constraints that may limit its adoption by utilities and community members. For example, new infrastructure at households is needed to enable storage, sensing, treatment, and trading water, and household participation may vary based on climate and economics. The research presented in this manuscript focuses on the performance of centralized infrastructure and takes a simulation-based approach to evaluate the effects on water savings, energy savings, nodal pressure, and water quality. Reclaimed water networks are designed to maintain pressures and flows, and performance of a smart water grid may decrease due to new flows associated with produced water. The ability of prosumers to contribute water to a non-potable water network is facilitated by household-level pump systems, and the introduction of these decentralized flows into a pipe network affects flows and pressures in the network. High pressures in the network can limit the contribution of water from households that must overcome pressure heads through small pumps, and low pressures may emerge in times of low production and high demands. This research also evaluates savings in energy and water associated with a smart water grid. Micro-trading can reduce demands for produced reclaimed water, resulting in water savings. The energy required to run household pumps across a network, however, must be compared with the energy requirements of treating and pumping water from a centralized facility.

(**a**) Conventional urban water infrastructure.

(**b**) Dual reticulation system.

(**c**) Smart water grid.

**Figure 1.** (**a**) Conventional urban drinking water, wastewater, and stormwater systems. (**b**) A dual reticulation system closes the loop in the urban water cycle by treating wastewater and providing it for non-potable household uses. Effluent flows from the wastewater facility are reduced. (**c**) A smart water grid increases water efficiency in the urban water cycle by allowing households to contribute rainwater to the dual reticulation system. Effluent and stormwater flows are reduced.

The goal of this manuscript is to explore the feasibility of a smart water grid based on the performance of the centralized infrastructure and energy demands. This research develops a simulation framework that couples agent-based modeling and hydraulic models to test energy consumption, water consumption, and nodal water pressure in a smart water grid. Agent-based models simulate the individual behaviors and interactions of a population of agents to explore emergent system-level dynamics [9,10]. Agent-based modeling has been applied in water resources management to simulate a population of water consumers as agents with the purpose of exploring the emergence of system-level performance due to micro-level interactions [11]. A few studies couple agent-based models with hydraulic simulation to explore how changes in household demands affect system-level performance, such as pressure and flow directions [12–14]. Further, agent-based modeling has been applied to simulate markets for trading natural resources [11,15–17], and recent research applied agent-based modeling to simulate how households trade solar generated energy in a peer-to-peer energy market [8]. In the formulation developed in this research, consumer households are simulated as agents that exert irrigation demands, and prosumer households are simulated as agents that store rainwater, and pump rainwater into a pipe network. A hydraulic model is developed of a reclaimed water network that serves a small community of non-potable water consumers and prosumers. Output from the agent-based model specifies flows into and out of the water network at each node, and these outputs are used as negative and positive demand patterns for the hydraulic model. The modeling framework is applied for an illustrative case study that was developed based on realistic infrastructure data. Water consumption, nodal pressure, and energy consumption are evaluated for the network of water users for scenarios with and without micro-trading. System performance is tested for 126 scenarios across different climates and concentrations of prosumers to explore how precipitation and participation affect feasibility. The results demonstrate that a smart water grid is feasible, generating energy and water savings that vary in magnitude based on local climate and the level of community participation.
