Using values-informed mental models to understand farmer, water manager, and scientist use and perceptions of hydrologic models

• Decision Support Systems are increasingly produced to support water management. • Science and nature values affect when and how that information is used for decisions. • Values for accuracy influence water decisions the most, followed by stewardship. Decision-support systems using environmental data and models are increasingly common, but not always adopted by the intended end-users. This disconnect may be partly due to different values related to nature and the scientific process. In this study, we assessed whether and to what extent real-world water decisions, supported by groundwater flow models, are influenced by epistemic values (scientific values including testability and usability) and nature values. We conducted and analyzed semi-structured interviews of ten water managers, five hydrologic model developers, and seven agricultural producers within a Groundwater Management District in south-central Kansas overlying part of the US High Plains aquifer. We then constructed values-informed mental models related to each group’s decisions. The epistemic value for accuracy was the most important value influencing water management decisions, especially short-term operational and long-term planning decisions. Stewardship was the second most important value influencing water management decisions, especially decisions related to conservation. Participants from all three stakeholder groups mentioned most values in interviews, but model developers mentioned accuracy, methodological soundness and testability significantly more often than agricultural producers and water managers. Our results highlight differences—and commonalities—in how decision-support systems influence decisions across types of users, as well as the importance of acknowledging the role individual values play in environmental policy decisions. Incorporating these insights into modeling processes and communications can help hydrologic modelers and data producers better align their work with the decision needs of end-users.