Rapid mass movements hazards such as mountain rivers (torrents) and snow avalanches put humans and material assets at risk with dramatic consequences. In a context of lacking knowledge about the natural phenomena, expertise is required to provide analyses for decision and risk management purposes using multi-disciplinary quantitative or qualitative approaches. Expert judgements depend on the availability, quality and uncertainty of information. At the end, phenomenon scenarios and decisions may very well rely on very uncertain and conflicting information without being able to really know what was completely true, imprecise, conflicting or simply unknown in the hypotheses leading to the result. This work analyses relations between information and decision including the integration of results in information systems. On one hand, it contributes to improve traceability and quality description of the expertise process and, on the other hand, it provides and analyzes multicriteria aid-decision tools able to consider information imperfection (uncertainty, imprecision) resulting from conflicting sources. Firstly, we analyze the ability of multi-criteria decision analysis to help risk assessment, including a diagnosis of existing empirical approaches developed to combine the risk components evaluations. On this basis, any hierarchical model can be transformed in an another one, keeping the same decision results and highlighting some new preferences views on the problem such as role and importance of scenarios based on aggravated criteria in the decision. Secondly, a framework mixing evidential reasoning and multi-criteria decision analysis (ERMCDA) combines qualitative and quantitative criteria on which more or less reliable and conflicting sources provide uncertain and imprecise evaluations. The Analytic Hierarchy Process (AHP) is used both to model the problem in a conceptual way and to elicit preferences between key criteria. Fuzzy Sets and Possibilities theories are used to transform quantitative and qualitative criteria into a common frame for Dempster-Shafer Theory (DST) and Dezert-Smarandache Theory (DSmT). At the end, multi-criteria decision-aid methods can be viewed as a valuable and alternative support for risk components evaluation. Traceability through easily understandable methodologies (hierarchical approaches, fuzzy numbers) and information imperfection assessments can be viewed not only as ways to improve the global quality of the expertise and decision processes but also as creating a new space for interaction between expertise and society. In addition to their technical interest, they may become unexpected but valuable support to an integrated risk management approach.
