%0 Journal Article %T Evaluation of River Self - Purification Behavior Using One - Dimensional Numerical Modeling %J Iranian journal of Ecohydrology %I Faculty of New Sciences and Technologies, University of Tehran %Z 2423-6098 %A Ghezelsofloo, Abbas Ali %A Eftekhari, Mobin %A Akbari, Mohammad %D 2021 %\ 03/21/2021 %V 8 %N 1 %P 29-43 %! Evaluation of River Self - Purification Behavior Using One - Dimensional Numerical Modeling %K : deterioration factor %K Kardeh River %K MIKE11 model %K pollution prediction %K Self-purification factor %R 10.22059/ije.2020.308851.1376 %X Due to the growth of surface water pollution, this study intends to evaluate the behavior of self-purification and pollution removal in rivers by using numerical modeling. In this research, using data and information provided by water sampling in the Kardeh River, in Mashhad as a source for supplying drinking water in Mashhad city, we have investigated the river quality monitoring processes using the MIKE11 numerical software. In this model, boundary conditions include discharge, pollution (Ecoli) and water level, which has been done through field measurements. Measurements were performed in two time periods, one in April 2014 (indicating the high water season of the year) and the other in August 2014 (indicating the low water season of the year) by taking 12 samples of Kardeh river. The resulted outcomes of this research show that Manning roughness coefficient with the help of hydraulic model calibration in the study period is 0.058 and the river decay coefficient for Ecoli parameter in the warm season with a diffusion factor of 20 and diffusion coefficient of 0.5 is 0.08 and in the cold season with a diffusion factor of 5 and diffusion coefficient of 2 equals to 0.207. According to the results, the effect of Manning coefficient in estimating pollution is 90% and the share of other parameters is 10% in total. In order to calibrate the model, sensitivity analysis was used, which concludes from the above sensitivity analysis that the Manning coefficient has a great effect on modeling the spread and transmission of contamination. %U https://ije.ut.ac.ir/article_80216_5d672bebe3a52141a58e45d9977a3d1f.pdf