Long- term Precipitation Prediction Using Statistical Downscaling Model

One of the most important problems in the management and planning of water resources is to forecast long-term precipitation particularly in arid and semi-arid regions. Climate Change affects local hydrology of different regions, through changes in the pattern of precipitation. In this study, the impact of climate change on the precipitation of Chatrood and Saadatabad Sirjan stations using HadCM3 model outputs under A2 and B2 scenarios and SDSM downscaling model was predicted for three periods of (2010-2039), (2040-2069) and (2070-2099).Then, according to statistical measures of model performance such as Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Nash-Sutcliffe efficiency (NS) the results of model were evaluated. The results indicated that the SDSM model had high performances in two stations. Moreover, amount of annual precipitation under A2 and B2 scenarios will be decreased by 10.02 and 8.87 mm at the Chatrood station and 16.51 and 14.09 mm at the Saadatabad station, relative to reference period, respectively until 2099.