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Information Journal Paper

Title

Operation of the non-linear Muskingum model in the prediction of the pollution breakthrough curves through the river reaches

Pages

  21-34

Abstract

 The Muskingum model in both types of the linear and non-linear is one the most common models in the Flood routing through the River reaches. The simplicity and being stepwise in calculating the exit Flood hydrographs are the advantages of this model. Because of the similarity between the shape of the Flood hydrograph and Pollution Breakthrough curves, it is tried to examine the applicability of the Non-linear Muskingum model in the prediction of the contaminant concentration in downstream of the River reaches. The field data series of the MONOCACY and ANTIETAM Creek Rivers which were gathered by USGS have been used. During the tests, Rhodamine was used and the concentration pollute graphs were acquired in the four and eight cross-sections of the mentioned Rivers, respectively. The triple sets of the model parameters have been extracted in each reach, then the BC curves have been simulated in each position using them. It is observed that this model can rebuild the dimensions of the exit BC curve properly but, it also has some limitations in the modeling of the convection term of the Pollution using average flow velocity. For its solution, the extracted BC curves have been transported along the time axis with the magnitude of  in which L is the reach length and u is the average flow velocity. Also, for a better understanding of the effects of the model parameters in the simulated concentrations, the sensitivity analysis has been performed and it is found that the parameters of the ,  and  are the most to less effective parameters in the concentration calculation, respectively. It was also found that the power parameter of this model (m) for Pollution transport fluctuates in the range (0.1-1.4) and has an average value of 0.85. The value of the weighted coefficient (x) was also obtained in the range (-1 to +1), but the frequency of values greater than zero was greater and its average value was reduced to 0.91.

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