University of Tehran Press Iranian Journal of Soil and Water Research 2008-479X 49 5 2018 11 22 Sensitivity Analysis of Two-Dimensional Pollution Transport Model Parameters in Shallow Water Using RSA Method Sensitivity Analysis of Two-Dimensional Pollution Transport Model Parameters in Shallow Water Using RSA Method 1119 1129 68202 10.22059/ijswr.2018.244628.667779 FA Mahdi Khorashadizadeh PhD Student of Civil Engineering, University of Sistan and Baluchestan, Zahedan, Iran Gholamreza Azizian Assistant Professor, Department of Civil Engineering, University of Sistan and Baluchestan, Zahedan, Iran Seyed Arman Hashemi Monfared Associate Professor, Department of Civil Engineering, University of Sistan and Baluchestan, Zahedan, Iran Abolfazl Akbarpour Associate Professor, Department of Civil Engineering, University of Birjand, Birjand, Iran Journal Article 2017 11 08 Understanding of the fate of temporal and spatial distribution of pollutionis an essential subject for prediction of damages, caused by pollution,  on the ecology of rivers and coastal areas. It is also necessary to provide efficient solutions for both pollution control and environmental protection. In this study, shallow water equations have been used to simulate pollution transport by 2-dimensional finite volume method. Calibration-modification and frequent changing of the amount of parameters is a known issue in hydraulic and hydrologic models. Therefore, it is necessary to utilize methods for sensitivity analysis and reduction of the parameters number to calibrate models. In this study, the RSA sensitivity analysis method was used for each parameter in which the ratio of sensitivity and cumulative distribution function for the sets of good and bad parameters are computed.. For this purpose, 5000 iterations from uncertainty domain of calibration parameters of pollution transport model in a Standard issue of shallow water were performed by using uncertainty algorithm GLUE. With enforcing the acceptable threshold values for the sumof square error index on the total simulation results, 1000 premier simulations were introduced as an efficient simulation. The corresponded set of parameters was considered as good set parameters and the others as bad set parameters. Thus, the sensitivity index was calculated for the Manning coefficient and the floor slope in the x and y directions. The comparison of sensitivity analysis of parameters based on the RSA methods and variation coefficient of parameters indicated that RSA is an efficient method for sensitivity analysis of model parameters. Understanding of the fate of temporal and spatial distribution of pollutionis an essential subject for prediction of damages, caused by pollution,  on the ecology of rivers and coastal areas. It is also necessary to provide efficient solutions for both pollution control and environmental protection. In this study, shallow water equations have been used to simulate pollution transport by 2-dimensional finite volume method. Calibration-modification and frequent changing of the amount of parameters is a known issue in hydraulic and hydrologic models. Therefore, it is necessary to utilize methods for sensitivity analysis and reduction of the parameters number to calibrate models. In this study, the RSA sensitivity analysis method was used for each parameter in which the ratio of sensitivity and cumulative distribution function for the sets of good and bad parameters are computed.. For this purpose, 5000 iterations from uncertainty domain of calibration parameters of pollution transport model in a Standard issue of shallow water were performed by using uncertainty algorithm GLUE. With enforcing the acceptable threshold values for the sumof square error index on the total simulation results, 1000 premier simulations were introduced as an efficient simulation. The corresponded set of parameters was considered as good set parameters and the others as bad set parameters. Thus, the sensitivity index was calculated for the Manning coefficient and the floor slope in the x and y directions. The comparison of sensitivity analysis of parameters based on the RSA methods and variation coefficient of parameters indicated that RSA is an efficient method for sensitivity analysis of model parameters. https://ijswr.ut.ac.ir/article_68202_ca7ff8b9a9c44a8525f51a082f74b0eb.pdf