Modeling Climate Variables of Rivers Basin using Time Series Analysis (Case Study: Karkheh River Basin at Iran)

Abstract

Stochastic models (time series models) have been proposed as one technique to generate scenarios of future climate change. Precipitation, temperature and evaporation are among the main indicators in climate study. The goal of this study is the simulation and modeling of climatic parameters such as annual precipitation, temperature and evaporation using stochastic methods (time series analysis). The 40-year data of precipitation and 37-year data of temperature and evaporation at Jelogir Majin station (upstream of Karkheh dam reservoir) in western of Iran has been used in this study and based on ARIMA model, The auto-correlation and partial auto-correlation methods, assessment of parameters and types of model, the suitable models to forecast annual precipitation, temperature and evaporation were obtained. After model validation and evaluation, the Predicting was made for the ten future years (2006 to 2015). In view of the Predicting made, the precipitation amounts will be decreased than recent years. As regards the mean of annual temperature and evaporation, the findings of the Predicting show an increase in temperature and evaporation.