%0 Journal Article %T Uncertainty Analysis of Infiltration Parameters of WinSRFR Furrow Irrigation Simulation Model with Monte Carlo Method %J Iranian Journal of Soil and Water Research %I University of Tehran %Z 2008-479X %A Soroush, Fatemeh %A Riahi Madvar, Hossien %D 2019 %\ 08/23/2019 %V 50 %N 4 %P 1007-991 %! Uncertainty Analysis of Infiltration Parameters of WinSRFR Furrow Irrigation Simulation Model with Monte Carlo Method %K Parameter Estimation %K Outflow runoff hydrograph %K Advance trajectory %K Uncertainty %R 10.22059/ijswr.2018.261848.667966 %X The infiltration parameters, used in the surface irrigation simulation models, are not measured directly and their estimations are difficult and uncertain. Therefore, after calibration of model parameters, the uncertainty due to error in the model and the strategies should be considered to reduce and control the uncertainty of the results. For this reason, Monte Carlo simulation approach has been used in this study. Nowadays, the Monte Carlo simulation approach is used as a simultaneous and integrated approach to identify different types of uncertainty with various objective functions. Therefore, this research was conducted to analyze the uncertainty of the simulation results of the runoff hydrograph and the advance trajectory modeled by the WinSRFR software by developing the posterior analysis of the infiltration equation parameters and simulation of 1000 Monte Carlo samples. The results of the analysis indicated a high degree of uncertainty (bandwidth over 4) in initial selection of furrow irrigation infiltration parameters, Nash-Sutcliff criteria was considered to district behavioral and non-behavioral simulations and the acceptable threshold value for NSE criteria defined as NSE>0.9. By applying NSE>0.9, the behavioral simulations were detected and used for uncertainty analysis of the model. The uncertainty analysis of the model was performed based on 5% and 95% confidence levels of behavioral simulations errors. In this case, the uncertainty band width (d-factor) of two response variables was less than one indicating a good calibration result. The results of uncertainty analysis showed that the uncertainty of model parameters wasconsiderably decreased with application of Monte Carlo method. Therefore, the use of this method in the modeling and management of surface irrigation systems is recommended. %U https://ijswr.ut.ac.ir/article_72508_262b29edb2ef8c4c0c38afa4b105f2ea.pdf