CV


Mohsen Pourreza Bilondi

Mohsen Pourreza Bilondi

Associate Professor

Faculty: Agriculture

Department: Water Science and Engineering

Degree: Doctoral

Birth Year: 1983

CV
Mohsen Pourreza Bilondi

Associate Professor Mohsen Pourreza Bilondi

Faculty: Agriculture - Department: Water Science and Engineering Degree: Doctoral | Birth Year: 1983 |

Assessment of MC&MCMC uncertainty analysis frameworks on SWAT model by focusing on future runoff prediction in a mountainous watershed via CMIP5 models

AuthorsMohsen Pourreza-Bilondi,Armin Ahmadi,Amir Hossein Aghakhani Afshar,Vahid Nourani,Ali Asghar Besalat pour
JournalJournal of Water and Climate Change
Page number1811-1828
Serial number11
Volume number4
IF1.044
Paper TypeFull Paper
Published At2019
Journal TypeElectronic
Journal CountryIran, Islamic Republic Of
Journal IndexJCR،Scopus

Abstract

The river situation in a dry or semi-dry area is extremely affected by climate change and precipitation patterns. In this study, the impact of climate alteration on runoff in Kashafrood River Basin (KRB) in Iran was investigated using the Soil and Water Assessment Tool (SWAT) in historical and three future period times. The runoff was studied by MIROC-ESM and GFDL-ESM2G models as the outputs of general circulation models (GCMs) in the Coupled Model Intercomparison Project Phase 5 (CMIP5) by two representative concentration pathway (RCP) scenarios (RCP2.6 and RCP8.5). The DiffeRential Evolution Adaptive Metropolis (DREAM-ZS) was used to calibrate the hydrological model parameters in different sub-basins. Using DREAM-ZS algorithm, realistic values were obtained for the parameters related to runoff simulation in the SWAT model. In this area, results show that runoff in GFDL-ESM2G in both RCPs (2.6 and 8.5) in comparing future periods with the historical period is increased about 232–383% and in MIROC-ESM tends to increase around 87–292%. Furthermore, GFDL-ESM2G compared to MIROC-ESM in RCP2.6 (RCP8.5) in near, intermediate, and far future periods shows that the value of runoff increases 59.6% (23.0%), 100.2% (35.1%), and 42.5% (65.3%), respectively

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