TY - JOUR T1 - The Effect of Climate change on the Zayandeh-Rud River Basin’s temperature using a Bayesian machine learning Soft Computing Technique TT - تأثیر تغییر اقلیم بر درجه حرارت حوضه آبریز زاینده‌رود با استفاده از محاسبات نرم یادگیری ماشینی بیزین JF - JSTNAR JO - JSTNAR VL - 21 IS - 1 UR - http://jstnar.iut.ac.ir/article-1-3327-en.html Y1 - 2017 SP - 203 EP - 216 KW - climate change KW - downscaling KW - emission scenarios KW - temperature KW - Zayandeh-Rud River Basin N2 - This study aims to investigate the changes of minimum and maximum temperature variables under the impact of climate change for time period of 2015-2100 in the Zayandeh-Rud River Basin. The outputs of 14 Global Climate Models (GCMs) under three green-house emission scenarios (RCP2.6, RCP4.5, and RCP8.5) are employed from the Fifth Assessment Report (CMIP5) of Intergovernmental Panel on Climate Change (IPCC). A novel statistical downscaling method using a Bayesian Relevance Vector Machine (RVM) is used to project the impact of climate change on the temperature variables at regional scale. The results of the weighting average of the GCMs show that the various models have different accuracy in the projecting the minimum and maximum temperatures in the study area. The results demonstrate that the MIROC5 and CCSM4 are the most reliable models in projecting the maximum and minimum temperatures, respectively. The highest increase for both maximum and minimum temperatures was obtained in winter. On the annual basis, the maximum temperature will increase by 0.18-0.76 °C and 0.25-1.67 °C, respectively, in the near and long-term future periods under different emission scenarios. The annual minimum temperature will increase by 0.28 to 0.82 °C and 0.24-1.56 °C, respectively, in the near and long-term future periods. In a general view, changes in maximum temperature will be slightly higher than minimum temperature changes in the future. M3 10.18869/acadpub.jstnar.21.1.203 ER -