Water conflicts in agricultural watersheds pose significant challenges for effective resource management. This study presents a novel approach to identifying potential water conflicts within water user organizations by integrating socio-hydrological data into an agent-based modeling tool, SHABM (Socio-Hydrological Agent-Based Model). The model simulates interactions between the Water Board, Canal Administrator, Farmers, and Crops, considering water distribution rates, crop water demands, farmer personalities, and irrigation infrastructure, among others. The study area is located in the Longaví River basin, Chile, and simulations were conducted from 2017 to 2022, considering various scenarios of canal lining and oversight levels. Results demonstrate the tool's ability to identify potential conflict areas and provide insights into the evolution of farmer decision-making. Integrating geospatial data, hydrological models, and social information proves crucial for achieving comprehensive water management and addressing complex water-related challenges in agricultural contexts. The SHABM tool has the potential to support decision-making processes and promote sustainable water governance in regions facing water scarcity and competing demands.