In mountain areas, natural phenomena such as snow avalanches, debris flows and rock-falls, put people and objects at risk with sometimes dramatic consequences. Risk is classically considered as a combination of hazard, the combination of the intensity and frequency of the phenomenon, and vulnerability which corresponds to the consequences of the phenomenon on exposed people and material assets. Risk management consists in identifying the risk level as well as choosing the best strategies for risk prevention, i.e. mitigation. In the context of natural phenomena in mountainous areas, technical and scientific knowledge is often lacking. Risk management decisions are therefore based on imperfect information. This information comes from more or less reliable sources ranging from historical data, expert assessments, numerical simulations etc. Finally, risk management decisions are the result of complex knowledge management and reasoning processes. Tracing the information and propagating information quality from data acquisition to decisions are therefore important steps in the decision-making process. In this paper, a global integrated framework is proposed to improve the risk management process in a context of information imperfection provided by more or less reliable sources. It includes uncertainty as well as imprecision, inconsistency and incompleteness. It is original in the methods used and their association: sequential decision context description, development of specific decision-making methods, imperfection propagation in numerical modelling and information fusion. This framework not only assists in decision-making but also traces the process and evaluates the impact of information quality on decision-making.