Document Type : Research Paper


1 PhD. Candidate, Faculty of Natural Resources, University of Tehran, Karaj, Iran

2 Assistant Professor, Faculty of Natural Resources, University of Tehran, Karaj, Iran

3 Professor, Faculty of Natural Resources, University of Tehran, Karaj, Iran In


In order to decrease the risks associated with the management of urban watersheds, the use of proper methods is an essential task to estimate the runoff with a high degree of confidence. Time of concentration is one of factors that impacts on peak discharge and runoff volume. The objective of this study is to select the best method among the empirical formulas for estimating the time of concentration. In this study, for determination of actual time of concentration, the field method based on measuring the travel time by using floating-object method was employed. To select the best empirical formula of the time of concentration, the statistical criteria including percentage Relative Error (RE), Root Mean square error (RMSE), Average percentage Relative Error (RME), Nash - Sutcliffe criteria (NS) and determination coefficient were used. Then, differences among the estimations obtained from empirical equations were compared with the actual values. The results of this study based on comparison of the relative error in each interval showed that in the reach No. 2, empirical formulas of California, Chow, Carter and Federal Aviation, with percentage error of 2.7, 2.9, 4.4 and 4.4 have showed the best estimation, respectively. The equation proposed by Kirby with percentage error of 1 in the reach No. 3, the equation of Ventura with percentage error 8.5 in the reach No. 9 and the equation of rational hydrograph with percentage error 4.8 in the reach No. 10 have showed the best estimates. Therefore, it is recommended to use the empirical formula that has the lowest percentage of error for areas with features similar to the studied reaches. In general, the results show that only rational hydrograph method in all of the reaches has the lowest error and then provides the most proper estimates compared than others.


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