TY - JOUR ID - 70294 TI - Analysis of the Uncertainty of the Simulation-Optimization Model using the Monte Carlo Markov Chain Algorithm JO - Iranian journal of Ecohydrology JA - IJE LA - en SN - 2423-6098 AU - Norouzi Khatiri, Khadije AU - Niksokhan, Mohammad Hossein AU - Sarang, Amin AD - Ph. D Student, School of Environment, College of Engineering, University of Tehran, Iran AD - Associate Professor, School of Environment, College of Engineering, University of Tehran, Iran AD - Assistant Professor, School of Environment, College of Engineering, University of Tehran, Iran Y1 - 2019 PY - 2019 VL - 6 IS - 1 SP - 137 EP - 151 KW - simulation-optimization KW - Groundwater KW - PSO KW - uncertainty DO - 10.22059/ije.2018.269045.976 N2 - Uncertainty analysis is an inseparable step in the process of hydrological modeling. Quantitative assessment of the uncertainty in the simulation model outputs and its parameters lead to an increase of confidence in the results of modeling and understanding of the sources of uncertainty.  Due to the increasing use of groundwater management model and predicting the behavior of the aquifer, this research is seeking to analyze the uncertainty in quantitative-qualitative aquifer simulation and its effect on optimization results. Using SWAT hydrologic model, the amount of recharge is specified and inserted into MODFLOW groundwater flow model and MT3DMS transmission model. In this research, the DREAM (zs) algorithm (based on Monte Carlo Markov chain algorithms) was used to examine the uncertainty of MODFLOW model parameters. Then by linking the model with MOPSO, the optimum head and salinity are obtained in the aquifer. The results show that the accuracy of the inputs of the model leads to the desirability of the results in relation to the intended purpose of reducing the water table. UR - https://ije.ut.ac.ir/article_70294.html L1 - https://ije.ut.ac.ir/article_70294_08ec385e68a099fba5b9c2ca3e500797.pdf ER -