We address the problem of multiple depot fleet dimensioning for delivery of a seasonal stochastic demand along a given period. Static and dynamic rules for the allocation of demands to depots are discussed. Given a predicted demand behavior represented by a generation function over time and space, distances between clients and the depots, cost to lease one vehicle for the period, unity cost for traveling a distance for leased and for short time hired vehicles and a demand allocation rule, find the (possibly heterogeneous) fleet size at each depot that minimizes the expected operation cost for the period. We propose a decomposition approach based on Stochastic Dual Dynamic Programming that allows dealing with the integrality of the subproblems. The resulting solution is then evaluated through simulation of the operation along the period via a Monte-Carlo method. The sensitivity to the quality of demand prediction and to the demand allocation rule is analyzed. Finally, we discuss implementation issues and the limits of the proposed method.