An accurate estimation of peak flow in data scarce watersheds is a challenging activity due to incorrect computation of time of concentration. The challenge of peak flow estimation basically comes from the estimation of watershed time of concentration (Tc). The challenge in estimation time of concentration estimation methods overcome the failures of infrastructures due to local flooding and conservative construction due to overestimate flood. This study is aimed for selection of the best equations that have best performance of the empirical equations for estimating the time of concentration of the studied experimental watersheds. The methodology of this research works on evaluating the performance of equations. This research is also access the equations performance to modifying them to reduce their error. So ranking-based selection method is developed for assessing and selecting the best performing methods. And modification work is basically done by introducing the correction factor into the existing equations. According to the study, TR-55 Model has (correction factor of 1.03), Brancby-william has (correction factor of 0.5), Kerby-Hathaway (correction factor of 1.60, NRCS kinematic has (correction factor of 0.9), Kirpich (1940) has (correction factor of 2.1), and Modified Kirpich has (correction factor of 2.560). The study shows that Win TR-55 model based Tc estimation and NRCS kinematic (1986) method are the most accurate, the main reason for the higher accuracy and correctness was the methods are used addition of the parameters like Manning's roughness coefficient, precipitation and the segments in different flow types (for the TR-55 model only). The observed Time of concentration values from hydrograph method for the study area has weak correlation with the area of the watershed(A), main stream length of the watersheds(L) and slope of watersheds(S).