Simulating Intra-Storm Variation of Runoff Coefficient Using Precipitation Components for Neyshabour Bar Watershed, Iran

Application of empirical methods in estimation of surface runoff is a must in ungauged watersheds. The runoff coefficient is one of the important input variables in empirical models. Proper calculation of runoff coefficient and study on its variation in different conditions facilitates proper estimation of runoff and flood peaks. So far, many studies have been conducted for estimation of runoff coefficient on monthly, seasonal and annual bases. However, limited researches have considered the variation of runoff coefficient during a storm event. The present study was therefore formulated to study on the intra variation of runoff coefficient and its affecting factors in Bar Neyshabour watershed comprising an area of 11388ha. Towards this attempt, 32 storm events, with duration of equal to or more than watershed concentration time of 2.9h and significant changes in hydrographs were selected from 440 events recorded during 1980 to 1989 and corresponding hydrographs and hyetographs were collected. The mean runoff coefficient and associated quarterly and deciles were also calculated. The relationships between different rainfall and excess rainfall with mean runoff coefficient and its components was then analyzed with the help of bivariate and multivariate regressions and applying ordinary and transformed data. The results of the study verified a dynamic drastic change from 0.6 to 45.7% in runoff coefficient with respective arithmetic, median, antilogarithm mean and standard deviation of 10.65, 7.96, 7.59 and 9.35%. In general, the results of the study also revealed the inter changes of runoff coefficient during storm events and feasibility of its simulation by using bivariate regression with correlation coefficient from 28 to 88% (0.003≤p≤0.68). It was also found that the 2nd and 3rd quartiles could estimate the runoff coefficient variability better than other rainfall components in the study watershed.