Mathematical optimization models can used to tackle Water Resource (WR) management problems with a multiperiod feature. Such models handle thousands of constraints and variables depending on the level of adherence required to reach a significant representation of the system. Moreover these problems are typically characterized by a level of uncertainty about the value of hydrological exogenous inflows and demand patterns. A WR model is usually defined in a dynamic planning horizon in which management decisions have to be made either sequentially, by adopting a predefined scenario independently. In this paper we present a scenario analysis approach to perform water system planning and management under climatic and hydrological uncertainty. Different generation techniques can be used to set up and analyze a number of scenarios. Uncertainty is modeled by a scenario-tree in a multistage environment, which includes different possible configurations of inflows in a wide time horizon. The aim is to indetify trends and essential features on which to base a robust decision policy.