In search auctions, when the total budget for an advertising campaign during a certain promotion period is determined, advertisers have to distribute their budgets over a series of sequential temporal slots (e.g., daily budgets). However, due to the uncertainties existed in search markets, advertisers can only obtain the value range of budget demand for each temporal slot based on promotion logs. In this paper, we present a stochastic model for budget distribution over a series of sequential temporal slots during a promotion period, considering the budget demand for each temporal slot as a random variable. We study some properties and present feasible solution algorithms for our budget model, in the case that the budget demand is characterized either by uniform random variable or normal random variable. We also conduct some experiments to evaluate our model with the empirical data. Experimental results show that the budget demand is more likely to be normal distributed than uniform distributed, and our strategy can outperform the baseline strategy commonly used in practice.