Exploring human-groundwater feedbacks in the Dutch agricultural context under climate extremes using an agent-based model

In recent years, the Netherlands has experienced extreme climatic events, including droughts in 2018 and 2022 and record-breaking wet years, such as 2024. These events are prompting a paradigm shift among water managers and users from rapidly draining water to holding it when possible to mitigate dry years, while maintaining the capacity to deal with floods. This research aims to examine how water users' decisions to adapt to drought can influence the water system, and vice versa, while accounting for trade-offs with flood risk. We address this research question using an agent-based model (ABM) based on a small agricultural catchment (Hupsel, ~1,400 ha) in which dairy farming is the predominant land use. The ABM has two main components: 1) the hydrological system; and 2) the human decision-making system. The hydrological system focuses on shallow groundwater and surface water, represented by a MODFLOW model that includes drainage and surface water networks, a single-layer sandy aquifer, and different land use types via the unsaturated zone flow (UZF) package. In the human decision-making system, farmers can decide among different adaptation options to drought based on the protection motivation theory: 1) adopt groundwater irrigation; 2) retain water in ditches to enhance recharge; 3) remove drains or ditches to enhance recharge further; and 4) change crops to less water-demanding ones. Results focused on irrigation indicate that consecutive years of drought lead to higher irrigation adoption, which, in turn, depletes the aquifer and makes the water system more sensitive to dry spells. ABMs are a valuable tool to explore the feedback between humans and the water system in a spatially explicit way, moving beyond the usual representation of anthropogenic interventions as model boundary conditions.