14147

12818

كارشناسي ارشد

آب

اصفهان : دانشگاه صنعتي اصفهان

1397

چهارده، [۹۶]ص.: مصور، جدول، نمودار

سعيد اسلاميان

محمد جواد زارعيان، حسين سقائيان نژاد

جهانگير عابدي كوپايي، حسين خادمي

1397/09/18

كتابنامه

كشاورزي

مهندسي كشاورزي

ID12818

Investigation of different downscaling methods uncertainty to predict the impacts of climate changes in Isfahan and Koohrang stations Safa Karimi sf karimi1990@gmail com Jun 12 2018 Department of Water Engineering College of Agriculture Isfahan University of Technology Isfahan 84156 83111 IranSupervisor S S Eslamian saeid@cc iut ac irProfessor Department of Water Engineering College of Agriculture Isfahan University ofTechnology Isfahan 84156 83111 Iran AbstractIncreasing industrial activity and consequently greenhouse gas emissions havedisturbed the global climate balance especially in recent years which is referred to asclimate change This phenomenon has affected various systems of human life therefore its investigation has become one of the most important scientific discussions in recentyears Since rainfall and temperature changes have a direct impact on water resources one of the main goals of the experts is to predict the future of the climate morerealistically The purpose of this study is to investigate the uncertainty of thedownscaling methods in Zayandeh rud basin For this purpose the output of the fivegeneral atmospheric circulation models which is the most credible tool for examiningthe effects of climate change were obtained from the fifth Assessment Report of theIntergovernmental committee on Climate Change for Isfahan and Koohrang stations forthe base period 1971 2000 the mid term 2006 2010 and the upcoming 2020 2049 forthree scenarios of RCP2 6 RCP4 5 and RCP8 5 By verifying the accuracy of theclimate parameters of each model in the mid 2006 2010 period it was found that eachGCM model alone has no ability to predict rainfall and temperature and it is better touse weighted models The results showed that the RCP8 5 Scenario for Isfahan Stationand RCP2 6 Senario for Koohrang Station stations are more consistent with realdata The weighted models were eventually introduced to the LARS WG downscalingmodels and the neural network Then their uncertainty was investigated using Bootstrapmethod The results showed that the rainfall parameter was more reliable thantemperature so that in most months especially in spring summer and autumn thepredicted precipitation was at 95 confidence range In the event that the confidencerange of the minimum and maximum temperature was lower and in most months thepredicted values were not considered at confidence ranges Also the results showed thatthe neural network did not have good ability to predict the minimum and maximumtemperatures and finally it was found that in the LARS model the number of months 98

سعيد اسلاميان

محمد جواد زارعيان، حسين سقائيان نژاد

جهانگير عابدي كوپايي، حسين خادمي