Effect of recorded data on hydroclimatological study in semi-arid zones

More accurate forecasting of monthly rainfall is significantly important in hydroclimatological studeis such as drought forecasting in agriculture, irrigation schedule, water resources management, and crop pattern design. In this paper, ability of time series models in forecasting the rainfall according to the climate conditions is estimated. For this purpose, rainfall data of four different climates in Iran was selected. Using the data amounts of rainfall were forecasted by time series models for one next year. In first method number of observation data for model calibration were 60, and then this increase to the 120 and 588 data. Time series models have found a widespread application in many practical sciences. In addition, rainfall forecasting is done by some methods such as time series models, satellite imagery, and artificial neural networks. However, according to the deficit data in most rainfall forecasting, number of required observation data always been questioned. Therefore, this paper attempts to present number of required observation data according to the climate conditions. By comparing R2 of the models, it was determined that time series models were better appropriate to rainfall forecasting in semi-arid climate. Number of required observation data for forecasting of one next year was 60 rainfall data in semi-arid climate

کلیدواژه ها:

: Hydroclimatological study ، Length of recorded data ، Rainfall forecasting ، Semi-arid zones ، Time series analysis