عنوان مقاله [English]
In the present study, the efficiency of the advection-dispersion equation in simulation of the pollution transport through the Gravel-Bed Rivers with Riffle-Pool bed-form was investigated. Experiments of tracer material (NaCl) were performed in a flume with a length of 11 m, width of 0.5 m and height of 0.7 m and with a longitudinal slope of 0.006 in three flow discharges (7.5, 10 and 12.5 lit/s). Four bed-forms of Riffle-Pool with different heights and wavelengths were considered to simulate hyporheic exchanges. The laboratory results were also simulated by the OTIS numerical model. The laboratory results showed that in bedless-form flow, increasing the flow rate increases the longitudinal dispersion coefficient. The opposite of this trend was observed at the presence of bed-form due to hyporheic exchanges. Increasing the height of the bed-form increases the Reynolds number in the hyporheic zone and consequently hyporheic exchanges increase and the longitudinal dispersion coefficient increases. Simultaneous increase of flow rate and the bed-form height causes excessive increase of hyporheic exchanges. Therefore, the residence time of the pollution in the sedimentary bed area is reduced and as a result, the pollution returns to the main flow area with less temporary storage in the storage zones. Therefore, increasing the longitudinal dispersion coefficient with increasing the bed-form height in the range of high flow rates is not significant. Increasing the wavelength of the bed-form also increases the residence time of contamination in the hyporheic zone, which increases the longitudinal dispersion coefficient. Increasing the flow rate reduces the role of hyporheic exchanges so that the main volume of pollution is transferred to the main flow area. Therefore, the effect of increasing the wavelength of the bed-form on the longitudinal dispersion coefficient decreases with increasing the flow rate. The comparison of laboratory results with numerical solution of OTIS model shows the high accuracy of this model in predicting the transmission of contamination.