This paper presents an optimization method to solve the short-term unit commitment and loading problem with uncertain inflows. A scenario tree is built based on a forecasted fan of inflows, which in turn comes from the precipitation forecast and the historical realizations of the inflows. The tree-building approach seeks to minimize the nested distance between the stochastic process of historical inflow data and the multistage stochastic process represented in the scenario tree. A two-phase multistage stochastic model is used to solve the problem. One of the main features of the modeling of the problem is that the effect of varying water head on production is carefully heeded. The proposed optimization is tested on a 30 day rolling horizon with daily forecasted inflows for three power plants situated in the province of Quebec, Canada, that belong to the company Rio Tinto.