University of TehranIranian Journal of Soil and Water Research2008-479X51420200621Parameters Uncertainty Analysis in Estimating Probable Maximum Flood in Bakhtiary Dam Basin by Monte Carlo MethodParameters Uncertainty Analysis in Estimating Probable Maximum Flood in Bakhtiary Dam Basin by Monte Carlo Method8558717450510.22059/ijswr.2020.291296.668365FAHoseinFathianDepartment of Water Resources Engineering, Faculty of Agriculture and Natural Resources, Ahvaz Branch, Islamic Azad University (IAU), Ahvaz, Iran.0000-0002-0555-4454ALI MOHAMMADAKHONDALIProfessor of Hydrology and Water Resources Engineering Department, Collage of Water Sciences Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.MohammadrezaSharifiAssistant prof, Hydrology and Water Resource Engineering, faculty of Water Sciences Engineering, Shahid Chamran Univrsity, Ahvaz, Iran.Journal Article20191031The reliability and validity of extreme floods, especially the probable maximum flood (PMF), requires to consider uncertainty sources in flood estimation. Parameters uncertainty of rainfall-runoff models are the main sources of uncertainty in flood estimation. In this paper, the Monte Carlo method has been used to estimate the PMF hydrograph uncertainty due to uncertainty in the calibration parameters of the rainfall-runoff model in Bakhtiary Basin in southwestern of Iran. The HEC-HMS hydrologic model was used to estimate the PMF hydrograph resulted by the probable maximum precipitation (PMP). The SCS curve number, Clark's unit hydrograph and Muskingum methods were used to model losses, rainfall-runoff transform and river flood routing, respectively. The results show that the uncertainty in peak discharge and volume of PMF hydrograph due to the uncertainty of all parameters are 17.13 and 6.79%, respectively. The results showed that the uncertainty in peak discharge and PMF hydrograph volume due to uncertainty of all parameters are 17.13 and 6.79 percent respectively. The uncertainty in peak discharge of PMF hydrograph due to curve number, initial losses, concentration time, Clark's storage coefficient, Muskingum K and Muskingum X parameters are 5.05, 0.4, 3.78, 3.85, 4.05 and 0.01 percent respectively. Also, the uncertainty in the PMF hydrograph volume due to the uncertainty of the curve number, initial losses, concentration time, Clark's storage coefficient, Muskingum K and Muskingum X parameters were 4.46, 0.332, 0.328, 1.6, 0.08 and 0.0002 percent respectively. Therefore, in order to reduce the uncertainty in estimating PMF hydrograph, it is necessary to be more precise in estimating the parameters of curve number, Muskingum K, Clark's storage coefficient and concentration time, respectively.The reliability and validity of extreme floods, especially the probable maximum flood (PMF), requires to consider uncertainty sources in flood estimation. Parameters uncertainty of rainfall-runoff models are the main sources of uncertainty in flood estimation. In this paper, the Monte Carlo method has been used to estimate the PMF hydrograph uncertainty due to uncertainty in the calibration parameters of the rainfall-runoff model in Bakhtiary Basin in southwestern of Iran. The HEC-HMS hydrologic model was used to estimate the PMF hydrograph resulted by the probable maximum precipitation (PMP). The SCS curve number, Clark's unit hydrograph and Muskingum methods were used to model losses, rainfall-runoff transform and river flood routing, respectively. The results show that the uncertainty in peak discharge and volume of PMF hydrograph due to the uncertainty of all parameters are 17.13 and 6.79%, respectively. The results showed that the uncertainty in peak discharge and PMF hydrograph volume due to uncertainty of all parameters are 17.13 and 6.79 percent respectively. The uncertainty in peak discharge of PMF hydrograph due to curve number, initial losses, concentration time, Clark's storage coefficient, Muskingum K and Muskingum X parameters are 5.05, 0.4, 3.78, 3.85, 4.05 and 0.01 percent respectively. Also, the uncertainty in the PMF hydrograph volume due to the uncertainty of the curve number, initial losses, concentration time, Clark's storage coefficient, Muskingum K and Muskingum X parameters were 4.46, 0.332, 0.328, 1.6, 0.08 and 0.0002 percent respectively. Therefore, in order to reduce the uncertainty in estimating PMF hydrograph, it is necessary to be more precise in estimating the parameters of curve number, Muskingum K, Clark's storage coefficient and concentration time, respectively.https://ijswr.ut.ac.ir/article_74505_f56b5da54385e6a498bca4f9b4ef8ed7.pdf