Sociohydrological Agent Besed Modeling Framework for Identifying and Addressing Water Conflicts

The present study introduces a methodology based on Socio-Hydrological Models Integrated with Agent-Based Models (SHABM) to identify and analyze potential water conflicts in the Longaví River Basin, Chile. This approach combines fieldwork to characterize user profiles, computational modeling, and simulations to explore interactions among water users, governance systems, and hydrological dynamics in a context of limited water resources.The Longaví River Basin is defined by a Mediterranean climate and a pluvial-nival regime that creates marked hydrological seasonality. These conditions, combined with significant agricultural dependency, generate tensions in water distribution. Addressing these conflicts requires tools that integrate technical, social, and environmental factors, which led to the development of the SHABM model.The SHABM model follows the ODD protocol (Overview, Design concepts, and Details) to ensure transparency and reproducibility. It models three main types of actors: the Water Board (WB), responsible for allocating volumetric water quotas; Canal Administrators (CA), who distribute water to users; and Farmers (F), who make individual decisions regarding water use. The model incorporates agent heterogeneity through variables such as personality, crop profitability, water use efficiency, and regulatory compliance.A key contribution of this study is the technological architecture, which uses a modular approach with Python for programming and MongoDB as a non-relational database management system. This architecture manages large data volumes, integrating geospatial, technical, and social information in real time. It also allows for adapting the model to different scenarios and basins, ensuring scalability and interoperability with other systems.Simulation scenarios were implemented under conditions of normal water availability, scarcity (-20%), and abundance (+20%), combined with different levels of institutional oversight (low, medium, high). Data sources included primary inputs, such as user surveys, and secondary inputs, including hydrological records from the Longaví River and crop characterizations.The results indicated that scenarios with low water availability and limited oversight promote conflict emergence, whereas stronger enforcement significantly reduces tensions. The model shows that behavioral patterns are influenced by agents’ personalities and the efficiencies of irrigation infrastructure and technologies.The SHABM model highlights critical areas in the basin where water distribution is most vulnerable to conflict. It also observes that self-serving agents are more likely to disregard distribution rules, amplifying inequalities among users.This study offers a replicable and scalable tool for analyzing socio-hydrological systems, supporting resource managers in exploring adaptive strategies and management scenarios. By integrating socio-hydrological models with ABM, the model captures detailed interactions between human and environmental factors. The technological architecture supports the modeling of complex systems and enhances result visualization and analysis, improving the understanding of patterns and decision-making processes.

Acknowledgments: ANID/FONDAP/1523A0001