<![CDATA[This research conducted to study the characteristics of daily rainfall and model making ofsynthetic daily rainfall in Pringsewu regency using periodic model, stochastic model and periodicstochastic models. This research conducted using daily rainfall data with length of 1984-2013from three rainfall stations, Pringsewu, Wonokriyo and Banyuwangi rainfall stations.These models performed by using 512 days annual data. Using rainfall frequency obtained andapplying the spectral method and the least squares method, it can be generated the daily rainfallperiodic models. Rainfall stochastic model assumed as the difference between rainfall data withperiodic rainfall models. Based on data from the series of stochastic, the component wascalculated using the approach of autoregressive models. Stochastic model was presented by usingthe autoregressive model of order three. Periodic stochastic model obtained by merging periodicmodel and stochastic model. Model validation and data obtained by calculating the correlationcoefficient. Based on the results of this research, it can be concluded that daily rainfall time seriescan be very significantly approximately recorded rainfall data. With the the average value ofcoefficient correlation of periodic model is 0.98019, coefficient correlation of stochastic model is0.99808, and coefficient correlation stochastic of periodic model is 0.99993keywords: daily rainfall, autoregresif models, stochastic component.]]>
