Agent-based modeling of participants' behaviors in an inter-sectoral groundwater market

While being affected by economic and hydrological conditions, the behaviors of water market participants can also be caused by their psychological characteristics and social stimuli of the environment. This paper employs agent-based modeling (ABM) approach to simulate a local groundwater market in central Iran. The proposed ABM framework couples social, economic, and hydrological sub-models. The social sub-model benefits from the theory of planned behavior under field studies to design psychology-based behaviors of trading agents. Moreover, in continuous interaction with the FlowLogo hydrological sub-model, the economic sub-model simulates the inter-sectoral water trading under a double-auction mechanism. The inter-sectoral trading includes selling the farms' irrigation water to the industry sector. The calibration and validation results for an eight-year simulation period (2010-2018) confirm the acceptable performance of the proposed ABM framework. Water trading patterns experience relatively extreme variations in the first years. However, with the adaption of the agents' bids to the market conditions, they gradually emerge in a more stable form in the last years. Furthermore, updating the psychological factors increases the agents' intention of participating in the market, and thus, the competition level over time. Finally, the hydro-economic analysis reveals that implementing the dynamic cap-and-trade policy increases the total net benefits of market participants by an average of 27% per year while reducing the region's groundwater drawdown by 56 cm. Such inter-sectoral water markets can help with the sustainable exploitation of groundwater resources.