*2.4. Agent-Based Modeling for Water Infrastructure*

Agent-based modeling simulates the behaviors and micro-interactions of a population of autonomous and heterogenous agents to model and study system-level phenomena [9,10]. Agent-based modeling has been applied to simulate a range of water resources planning problems by representing water users, stakeholders, and decision-makers as agents to capture decisions and behaviors around water use, water supply, wastewater services, and stormwater runoff [11]. Agent-based models have been applied to represent a population of residential water users that adapt their water consumption based on economics, climate, policies, and social influence [61–71]. These models simulate household decisions to use water and reduce consumption by adopting water-efficient technologies and restricting water use. Some frameworks couple agent-based modeling with the water supply system to capture feedback between the availability of water resources and decisions to conserve water [64–67,70]. Other agent-based models couple a population of agents with the hydraulic simulation of a water distribution system to evaluate how network flows are impacted by changing demands. Models capture water use changes during a water supply contamination event, based on exposure to the contaminant, communication from public officials, and social influence of peers [12,13,72–77]. Another set of studies uses agent-based modeling coupled with hydraulic simulation to evaluate how flows in a reclaimed water network and a potable water network change as customers adopt or resist water reuse programs [14,27,78]. Agent-based modeling has also been applied to model trading within natural resource markets, where agents use cost information to seek trades, negotiate, and adapt their preferences for trading permits with other agents. A few modeling studies couple an agent-based model with a water quality simulation model to assess water quality impacts of permit-trading strategies on river and estuary systems [11,15]. Other agent-based models capture the decisions of polluters to bid and sell permits in an emissions market, and these models are applied to assess the effect of trading on air quality [16,17]. More recently, an agent-based modeling was applied to simulate peer-to-peer markets by modeling households as agents that buy and sell energy in a residential smart energy grid [8]. In the research presented in this manuscript, agent-based modeling is loosely coupled with hydraulic simulation modeling to assess network performance metrics that are affected by agent behaviors to trade water. A simple market is simulated, where consumer agents buy rainwater when it is needed for irrigation, and prosumer agents meet demands when they have rainwater that is stored. The price of rainwater is not considered in this simulation, because the focus of the model is on the hydraulic feasibility of the network when trades are made. Additional research is needed to develop cost information and simulate how households make decisions to participate, bid, and execute micro-trades in a rainwater market.
