This paper addresses the challenges in risk management of complex depollution systems, marked by intricate interactions and emergent behaviors. The objective is to develop a comprehensive approach to risk management, accounting for the system's complexity and interconnectedness throughout the depollution project lifecycle. By employing a Model-Based Systems Engineering (MBSE) method using metamodels and models, the representation and analysis of multidisplinary components and their interactions are streamlined. The depollution system is modeled with stakeholders integrated as agents using Domain Specific Modeling Language (DSML). MBSE enables the examination of internal interactions and the evaluation of feasibility. Ultimately, this work aims to enhance depollution management by helping stakeholders assess feasibility, cost, and delay of depollution processes by effectively addressing risk management.