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Runoff coefficient (RC) is one of the important parameters, which is often considered in surface runoff and peak flood discharge estimation methods in various projects of watershed management and flood control. However, the effect of variability of RC due to human-induced activities on hydrologic behavior of the watershed has not been adequately considered globally. Therefore, the present research was carried out using 18 hyetographs and their corresponding hydrographs during 1984 to 2012 after considering the existence of suitable Landsat 7 (ETM+ and TM) satellite images with corresponding storm events for the Amameh Watershed located in Tehran Province, Iran. The object-oriented classification method was used to derive land use maps from satellite images. Afterward, four time periods were determined based on mean and standard deviation of residential area variations. The temporal distribution pattern of RC was then derived using a ranking method. The one- and two-way analyses of variance were also used to investigate the effect of residential area and rainfall variables on RC. Relationships among residential area as well as rainfall variables as independent variables and mean RC storm-wise as dependent variable were then modeled using two and multiple linear regressions. The results showed that RCs reduced in order of third, second, fourth, and first quartiles with respective values of 42.4, 38.2, 15.8, and 3.6%. The results also showed that RCs in the second and first quartiles and in the third and fourth quartiles were non-significantly decreased and increased by increasing of residential area, respectively. So that the highest variations occurred in first quartile with slope of - 144%. The results further proved that rainfall amount, phi index, and residential area with respective standardized regression coefficients (beta) of 0.629, - 0.465, and - 0.108 had the highest controlling effects on RCs. The finding of the current research proved the temporal variability of RCs at storm scale with more determinant effectiveness of rainfall properties than urbanized interferences. It helps hydrologists and watershed mangers designate appropriate strategies leading to proper implementations of developmental projects.