In a hydropower system, inflow is an uncertain stochastic process that depends on the meteorology of the reservoir's location. To properly utilize the stored water in reservoirs, it is necessary to have a good forecast or a historical inflow record. In the absence of these two pieces of information, which is the case in Ethiopia and most African countries, the derivation of the synthetic historical inflow series with the appropriate time resolution will be a solution. This paper presents a method of developing synthetic historical inflow time series and techniques to identify the stochastic process that mimics the behavior of the time series and generates inflow scenarios. The methodology was applied to the Ethiopian power system. The time series were analyzed using statistical methods, and the stochastic process that mimics the inflow patterns in Ethiopia was identified. The Monte Carlo simulation was used to generate sample realizations of random scenarios from the identified stochastic process. Then, three cases of inflow scenarios were tested in a deterministic simulation model of the Ethiopian hydropower system and compared with the actual operation. The results show that the generated inflow scenarios give a realistic output of generation scheduling and reasonable reservoir content based on the actual operation.